Systems and methods for identifying payor location based on transaction data

ABSTRACT

Systems and methods are described for building, maintaining, and using a repository of information about payors of second-party checks presented at a check-cashing entity for cashing. In various embodiments, the repository comprises stored information useful for determining the location of a payor of a second-party check. In one embodiment, information from the check that identifies an account on which the check is drawn, such as magnetic ink character recognition (MICR) line information from a paycheck, is used to access a repository of employer location information. In one embodiment, the payor location information is used to determine a proximity between the payor location and the check cashing entity location. In one embodiment, when a check is presented for which stored payor location information is not available, identifying information about the payor and/or the payor location is requested and is added to the repository.

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention relates generally to risk assessment, and, moreparticularly, to systems and methods for evaluating risk variablesassociated with financial transactions.

2. Description of the Related Art

Checks continue to be a popular medium of financial exchange. Manyindividuals who receive paychecks from their employers or checks fromother check issuers may not have a demand deposit account (DDA), such asa checking account in which to deposit their checks, or may prefer tocash their checks rather than depositing them in a bank account beforewithdrawing the funds. For example, many people prefer to cash theirpaychecks at a grocery store or check-cashing establishment.

The Financial Service Centers of America (FiSCA), the professionalorganization for the check cashing industry estimates that 6,000neighborhood financial service centers cash 180 million checks annually,with the aggregate face value of checks cashed over $55 billion.Furthermore, Dove Consulting estimated that in 2000 there were 9,500check cashing outlets with an additional 1,300 businesses that offeredcheck cashing as a secondary line of business. A large portion of theclientele at these locations are individuals who do not themselves havebank accounts, a segment of the population sometimes referred to asbeing “unbanked.”

Businesses that cash checks for their customers take a risk that theymay not be able to successfully cash the checks they have accepted.Forged checks, stolen checks, checks that have been fraudulentlyaltered, and checks written on accounts with insufficient funds or onaccounts that have been closed may contribute to losses sustained byentities that agree to cash checks for individuals.

A check that is written by one party for cashing by another party isoften known as a “second-party check.” For example, a payroll checkissued by an employer to an employee and presented by the employee forcashing at a supermarket, other retailer, or non-bank financialinstitution (NBFI) may be classified as a second-party check. Businessesthat cash second-party checks face extra difficulties in assessing therisk of such transactions because they often wish to assess thetrustworthiness of the person presenting the check for cashing as wellas the party that wrote the check, the payor, who is not typicallypresent.

Assessing the “unbanked” may be additionally difficult becausehistorical information about their check-related activities may besparse or unobtainable. Thus, unbanked individuals may have theircheck-cashing requests, and especially their second-party check-cashingrequests, denied more frequently than do individuals with known bankaccounts.

Various measures may be implemented by check-cashing entities to reducethe incidence of fraud. For example, check-cashing entities may consultpositive pay files before agreeing to cash a check. Positive pay filesare lists provided by check issuers, such as employers, of informationabout checks that they have issued. Finding a record in a positive payfile that matches a check presented to a check-cashing entity and thatindicates that the check has not yet been cashed may serve to increaseconfidence in the legitimacy and “cashability” of the check. Finding arecord in a positive pay file that matches a check presented to acheck-cashing entity and that indicates that the check has already beencashed may serve to increase suspicion in the fraudulent nature of thecheck and may decrease confidence in the “cashability” of the check.Thus, positive pay information can, in some circumstances, be useful forcheck-cashing entities. However, positive pay information is not alwaysavailable for a presented check and is not always accessible to acheck-cashing entity that is considering cashing the check.

As another example of measures that may be implemented to reduce theincidence of fraud, biometric input for identifying the individualpresenting a check may be used as a basis for accepting or declining aproposed check-cashing transaction.

Various methods for assessing risk associated with aspects of acheck-cashing transaction exist that can be used in a binary fashion toaccept or to decline a proposed transaction, but are not useful forexpressing intermediate levels of uncertainty regarding risk associatedwith aspects of the transaction or for generating a risk assessment thatis able to integrate a wide variety of relevant, but sometimescontradictory, risk assessment information.

In spite of currently available measures to avoid fraudulenttransactions, businesses that cash second-party checks and othernon-cash financial instruments continue to sustain losses that could beavoided with enhanced risk assessment.

SUMMARY

Effective new systems and methods are described for use in conjunctionwith an enhanced risk assessment of a proposed second-partycheck-cashing transaction, wherein the assessment is based at least inpart on location-related information associated with the transaction.For example, in some embodiments, a payroll check presented to acheck-cashing entity for cashing may be assessed as being of lower riskwhen an employer who has issued the payroll check is a local employerrather than when the employer is located at a greater distance from thecheck-cashing entity. Embodiments of systems and methods are describedthat allow a check authorization system to use information obtained inassociation with a proposed check-cashing transaction to identify alocation associated with the payor of a presented check.

Systems and methods are described for building, maintaining, and using arepository of information about payors of second-party checks presentedat a check-cashing entity for cashing. In various embodiments, therepository comprises stored information useful for determining thelocation of a payor of a second-party check. In one embodiment,information from the check that identifies an account on which the checkis drawn, such as magnetic ink character recognition (MICR) lineinformation from a paycheck, is used to access a repository of employerlocation information. In one embodiment, the payor location informationis used to determine a proximity between the payor location and thecheck cashing entity location. In one embodiment, when a check ispresented for which stored payor location information is not available,identifying information about the payor and/or the payor location isrequested and is added to the repository.

In various embodiments, location-based information about the presentedcheck may be expressed as a gradated location-based risk score thatreflects a degree of confidence in the likelihood of the check-cashingentity successfully settling the check with the issuing bank. Thelocation-based risk score may be combined with risk scores that aredescriptive of other aspects of the proposed check-cashing transactionand may be used to generate an accept/decline recommendation for thetransaction.

Various features of the invention provide check-cashing entities withsystems and methods for approving a greater portion of legitimateproposed check cashing transactions without incurring a correspondingincrease in losses due to returned checks or fraud. The enhanced riskassessment systems and methods described herein may thus encourage theproliferation of locations willing to cash second-party checks, mayallow check-cashing entities to keep their service fees low, and mayease the process of check cashing for persons presenting legitimatesecond-party checks. Thus, the new systems and methods serve to benefitboth the check-cashing entities and those presenting the checks.

An embodiment of a method is described for compiling acomputer-accessible repository of employer location information for usein assessing the risk of a payroll check-cashing transaction. The methodcomprises the acts of identifying employers in a desired geographicallocation and obtaining from the employers identifiers for checkingaccounts associated with the employers, wherein the checking accountsare accounts drawn on by the employers for writing payroll checks. Themethod further comprises compiling a repository of records on acomputer-accessible storage medium, wherein a record comprisesinformation to identify an employer location and at least one of: anassociated employer name and the associated employer checking account.In response to receiving a request to cash a payroll check for which therepository of records does not hold associated employer information, themethod further comprises requesting from a check-cashing entity that isprocessing the request information about at least one of: an employername, an employer bank account identification, and employer locationinformation. The method further comprises adding the employerinformation received from the check-cashing entity to the repository.

An embodiment of a method is described for compiling acomputer-accessible repository of check-issuer location information foruse in check transaction risk assessment. The method comprises the actsof: identifying check issuers in a desired geographical location,obtaining from the check issuers identifiers for checking accounts thatare associated with the check issuers, and compiling on acomputer-accessible storage medium a repository of records, wherein arecord comprises information to identify a check issuer name, anassociated check issuers location, and the associated check issuerschecking account.

An embodiment of a computer-accessible storage medium is described thatstores records of information about check issuers and records ofinformation about check-cashing entities, wherein a record about a checkissuer comprises a check issuer identifier and location information thatis associated with the check issuer, and a record about a check-cashingidentity comprises an identifier for the check-cashing identity andlocation information associated with the check-cashing identity.

An embodiment of a method of accessing location information for a checktransaction is described. The method comprises the acts of obtainingfrom a check information about an account associated with the check andusing the account information to access stored information about a payorassociated with the account and about a payor location.

An embodiment of a method is described for compiling acomputer-accessible repository of location information about issuers ofnegotiable instruments. The method comprises the acts of: identifyingissuers of negotiable instruments in a desired geographical location,obtaining identifiers associated with negotiable instruments from theissuers of the negotiable instruments, and compiling a repository ofrecords on a computer-accessible storage medium, wherein a recordcomprises information to identify a name associated with an issuer ofnegotiable instruments, an associated issuer location, and theassociated identifiers associated with the negotiable instruments.

An embodiment of a computer-accessible storage medium is described,wherein the storage medium stores records of information about issuersof negotiable financial instruments and records of information aboutcheck-cashing entities. A record about an issuer of a negotiablefinancial instrument comprises an issuer identifier and locationinformation associated with the issuer. A record about a check-cashingidentity comprises an identifier for the check-cashing identity andlocation information associated with the check-cashing identity.

An embodiment of a system is described for compiling acomputer-accessible repository of check issuer location information foruse in check transaction risk assessment. The system comprises means foridentifying check issuers in a desired geographical location and meansfor compiling a repository of records on a computer-accessible storagemedium, wherein a record comprises information to identify a checkissuer name, an associated check issuer location, and an associatedcheck issuer checking account, and wherein the checking account is anaccount drawn on by the check issuer for issuing checks.

An embodiment of a computer-accessible storage medium is described thatcomprises information that associates check issuer bank accountinformation with check issuer location information and check-cashingentity location information.

For purposes of summarizing the invention, certain aspects, advantagesand novel features of the invention have been described herein. It is tobe understood that not necessarily all such advantages may be achievedin accordance with any particular embodiment of the invention. Thus, theinvention may be embodied or carried out in a manner that achieves oroptimizes one advantage or group of advantages as taught herein withoutnecessarily achieving other advantages as may be taught or suggestedherein.

BRIEF DESCRIPTION OF THE DRAWINGS

A general architecture that implements various features of the inventionwill now be described with reference to the drawings. The drawings andthe associated descriptions are provided to illustrate embodiments ofthe invention and not to limit the scope of the invention. Throughoutthe drawings, reference numbers are re-used to indicate correspondencebetween referenced elements.

FIG. 1 is a block diagram of one embodiment of a system to authorize theacceptance of second-party checks.

FIG. 2 is a flowchart depicting one embodiment of a process to authorizethe acceptance of second-party checks.

FIG. 3 is a diagram that depicts one embodiment of a set of factors usedto generate a transaction risk score for acceptance of a second-partycheck.

FIG. 4 depicts four examples of risk score calculations for second-partycheck transactions.

FIG. 5 shows one embodiment of a repository of positive pay information.

FIG. 6A is a block diagram of one embodiment of a system that usespositive pay information to generate a risk score for second-party checkacceptance.

FIG. 6B is a block diagram of a second embodiment of a system that usespositive pay information to generate a risk score for second-party checkacceptance.

FIG. 7A is a block diagram of one embodiment of a system to accessexternally stored positive pay information.

FIG. 7B is a block diagram of one embodiment of a system to accessinternally stored positive pay information.

FIG. 8 is a flowchart that depicts one embodiment of a process that usespositive pay information to generate a risk score for second-party checkacceptance.

FIG. 9A is a block diagram of one embodiment of a system that usesbiometric information to generate a risk score for second-party checkacceptance.

FIG. 9B is a block diagram of a second embodiment of a system that usesbiometric information to generate a risk score for second-party checkacceptance.

FIG. 9C is a block diagram of a third embodiment of a system that usesbiometric information to generate a risk score for second-party checkacceptance.

FIG. 9D is a block diagram of a fourth embodiment of a system that usesbiometric information to generate a risk score for second-party checkacceptance.

FIG. 10 is a flowchart that depicts one embodiment of a process thatuses biometric information to generate a risk score for second-partycheck acceptance.

FIG. 11A is a block diagram of one embodiment of a system that useslocation-related information to generate a risk score for second-partycheck acceptance.

FIG. 11B is a block diagram of a second embodiment of a system that useslocation-related information to generate a risk score for second-partycheck acceptance.

FIG. 11C shows one embodiment of a repository of location-relatedinformation about check issuers.

FIG. 12 is a flowchart that depicts one embodiment of a process thatuses location-related information to generate a risk score forsecond-party check acceptance.

FIG. 13A is a block diagram of one embodiment of a system that usesinsignia-related information to generate a risk score for second-partycheck acceptance.

FIG. 13B is a block diagram of a second embodiment of a system that usesinsignia-related information to generate a risk score for second-partycheck acceptance.

FIG. 13C is a block diagram of a third embodiment of a system that usesinsignia-related information to generate a risk score for second-partycheck acceptance.

FIG. 14 is a flowchart that depicts one embodiment of a process to useinsignia-related information to generate a risk score for second-partycheck acceptance.

DETAILED DESCRIPTION OF THE EMBODIMENTS

Check fraud is a severe problem within the check cashing and payday loanindustries. Check cashing may refer to exchanging a business payroll orinsurance check, a government payroll or benefit check, a personal checkor other check for at least one of: money, goods and/or services. Paydayloan checks refer to a specific subset of personal checks that arecashed for money and are post-dated, often for about two weeks from thecheck-cashing transaction date. Check-cashing entities and otherbusinesses that offer at least one of check cashing and payday loancheck cashing services typically do so for a fee, which may be a flatfee per item, such as $3.00 per check, or may be a percentage of thecheck item's face value, such as 1% of the face value of the check, ormay be determined according to another method.

Various features of the invention provide general check-cashing andpayday loan check-cashing entities with systems and methods forapproving a greater portion of legitimate proposed check-cashingtransactions without incurring a corresponding increase in losses due toreturned checks or fraud. More accurate risk assessment for proposedcheck-cashing transactions may be carried out by considering a varietyof factors that reflect the trustworthiness of a person who presents acheck and the legitimacy of the check item itself.

For example, risk assessment for proposed check-cashing transactions maybe enhanced by a more accurate assessment of the trustworthiness of thecheck presenter, which may be based at least in part on validating thatthe person is who he/she claims to be. This can be done, for example, byusing biometric information obtained from the check presenter as afactor in a risk score calculation. For example, an individual whointends to cash checks at a check-cashing entity may “register” byproviding a biometric sample and variety of additional self-identifyinginformation. Subsequently, when the individual presents a check forcashing at a retailer point of sale or other check-cashing entitylocation, biometric information obtained from the check presenter at thetime of presentment may be compared with stored biometric informationfrom the time of registration in order to verify the identity of thecheck presenter. Biometric data from a check presenter, one type ofperson validation data, when compared with a trusted source of biometricdata, may yield a perfect or near-perfect match, a clear mismatch, or anintermediate level of confidence in the correct identification of thecheck presenter, which may be converted to a biometric risk score. Thebiometric risk score may then be combined with other risk factor scorespertaining to the check presenter, to the check item, and to thelocation of the check-cashing transaction to generate an overall riskscore for the proposed check-cashing transaction, as will be describedin greater detail below.

As another example, a more accurate risk assessment associated with aproposed check-cashing transaction may evaluate the authenticity of thecheck item offered for cashing and may be based, at least in part, ondata associated with the check item, such as positive pay information,which is sometimes available from a party who has written or issued thecheck. Positive pay information, when available, lists information aboutchecks that a check issuer has written and that may be compared toinformation from the check that is being presented for cashing. Forexample, information such as payee name, check number, check amount,and/or check issue date obtained from the presented check item at apoint of sale or other check-cashing entity location may be comparedwith information stored in a positive pay list, as will be described ingreater detail below. When information from the check item is comparedwith positive pay data it may yield a clear match, a clear mismatch, oran assessment of confidence in the correct identification of the checkitem that is less than clear. A positive pay risk or confidence scorebased on the comparison of the check item to the positive payinformation may reflect a level of confidence in the correctidentification of the check item. The positive pay risk score may thenbe combined with other risk factor scores associated with the proposedcheck-cashing transaction to generate a combined risk score for theproposed check-cashing transaction, as will be described in greaterdetail below.

Another form of risk assessment that aims to evaluate the legitimacy ofa check or other negotiable instrument presented for cashing may bebased on watermarks, insignia, security numbers, or other authenticatingmarks from the face or the back of a check or other negotiableinstrument. Authenticating marks are indicia that are typicallydifficult to reproduce illegitimately and that may thus be relied uponto help ensure the legitimacy of a negotiable instrument. Informationabout one or more such insignia or authenticating marks obtained from acheck presented for cashing at a point of sale or other check-cashingentity location may be compared to stored information about expectedconfigurations for the marks to yield a clear match, a clear mismatch,or an assessment of confidence in the correct identification of thecheck item that is less than clear. An insignia-related risk orconfidence score based on the comparison of the check item to theexpected configuration may reflect a level of confidence in the correctidentification of the check item. The insignia-related risk score maythen be combined with other risk factor scores associated with theproposed check-cashing transaction to generate a combined risk score forthe proposed check-cashing transaction, as will be described in greaterdetail below.

As another example, a more accurate assessment of the cashability of thecheck item may, additionally or alternatively, be based at least in parton information about the proximity of the check-cashing entity'slocation to the location of the check issuer, or on other location-basedinformation. For example, in some embodiments, based in part oncharacteristics of the check-cashing entity, checks issued by checkissuers located at a greater distance from the check-cashing entity mayexhibit a higher frequency of associated cashing problems. Thus, alocation-related risk score may be assigned to a proposed transactionbased on the proximity of the check-cashing entity to the check issuer'slocation. The location-related proximity risk score may be combined withother risk factor scores to generate an overall risk score for theproposed check-cashing transaction, as will be described in greaterdetail below.

Various embodiments of a check authorization system with enhanced riskassessment features are described. Information obtained by acheck-cashing entity in association with a proposed check-cashingtransaction may be transmitted to a check authorization system whichuses at least some of the information to calculate a risk score for theproposed transaction. In some embodiments, based at least in part on thecalculated risk score, the check authorization system may authorizeacceptance of the check for cashing or may recommend or provide anindication that the check-cashing entity accept or decline the proposedcheck-cashing transaction.

As will be apparent to one of ordinary skill in the art, many of thedisclosed features may be used without others, and may be implementeddifferently than described herein. For example, although describedprimarily in the context of a point-of-sale check cashing environmentfor second-party checks, the various inventive features are also usefulin other situations in which an entity accepts an unknown financialinstrument, such as may occur in an accounts receivable or remittanceenvironment. Furthermore, although described with respect to an“individual” presenting a check for cashing, the systems and methods mayapply to a group or other entity wishing to cash a financial instrument.The following description is thus intended to illustrate, and not tolimit the claimed systems and methods.

Risk Scoring for Checks and Other Negotiable Instruments

FIG. 1 is a block diagram of one embodiment of a system 100 to authorizeacceptance of second-party checks. As shown in FIG. 1, a check presenter101 presents a check to a check-cashing entity 110. In the embodimentshown, the check-cashing entity 110 requests approval for thetransaction from a check authorization system 100. In one preferredembodiment, if the check authorization system 100 approves thetransaction, the check-cashing entity 110 may accept the check and paythe check presenter 101 an equivalent amount of cash, minus any feesassociated with the transaction. In other embodiments, if the checkauthorization system 100 approves the transaction, the check-cashingentity 110 may accept the check in exchange for goods and/or services,for a combination of goods and/or services and cash, or for deposit. Asused herein, the term “cashing” is used to signify accepting the checkfor any combination of cash, goods, services, credit, or the like.

The check presenter 101 may be an individual wishing to cash a paycheckor other check. In other embodiments, the check presenter 101 may beanother type of entity, such as a company or corporation, a non-profitorganization, group of individuals, or other entity that has a check orother negotiable financial instrument to be cashed.

In various embodiments, the check to be cashed is a payroll check beingcashed by an employee. In other embodiments, the check presenter 101 maywish to cash a different type of check or negotiable financialinstrument, such as, but not limited to: a personal check, a corporatecheck, company insurance refund check, a government check, such as a taxrefund check, Social Security check, payroll check, or othergovernment-issued check, a traveler's check, bank check, official check,convenience check, money order, second-party check or other obligation,third-party check, value-carrying paper, or other type of cashablefinancial instrument. It is to be understood that the use of the term“check” in the context of this disclosure may refer to any of the aboveor other types of financial instrument.

In some embodiments, the check-cashing entity 110 may be a grocerystore, convenience store, or other retail or merchant facility thatwishes to provide second-party check cashing services to its customersat points of sale, at specialized kiosks, or at other locations withinthe merchant facility. In other embodiments, the check-cashing entitymay be a pawnshop, resort, casino, or other establishment that wishes tomake cashing checks convenient for its patrons. In still otherembodiments, the check-cashing entity 110 may be a financial institutionor non-bank financial institution (NBFI) such as a specialized businessthat offers check-cashing or money exchange services to individualswishing to cash checks, possibly along with related services such aspayday loans, local and overseas money wiring, and the like. In someembodiments, the check-cashing entity 110 may be a kiosk, stand, orother manned or unmanned location configured to provide check-cashingservices.

In the embodiment shown in FIG. 1, the check-cashing entity 110comprises one or more computer processors. In various embodiments, thecomputer processor is one of a wide variety of point-of-sale devices,such as an Eclipse terminal. The computer processors may comprise, byway of example, personal computers (PCs), mainframe computers, otherprocessors, program logic, or other substrate configurationsrepresenting data and instructions, which operate as described herein.In other embodiments, the processors may comprise controller circuitry,processor circuitry, processors, general purpose single-chip ormulti-chip microprocessors, digital signal processors, embeddedmicroprocessors, microcontrollers and the like.

In various embodiments, the check-cashing entity 110 may comprise adisplay for communicating a message to an operator at the check-cashingentity 110, such as instructions for working with the checkauthorization system 100, a message received from the checkauthorization system 100, and the like.

In the embodiment shown in FIG. 1, the check-cashing entity 110comprises one or more data input devices 115 for obtaining dataassociated with the proposed check-cashing transaction from the checkpresenter 101 and from the check. For example, the data input devices115 may comprise a check-scanning device for scanning an electronicimage of the check or of another document. The data input devices 115may comprise a device configured to read a magnetic ink characterrecognition (MICR) line from the face of the check or other document.The data input devices 115 may comprise a graphic device or systemconfigured to obtain information about a watermark, barcode, insignia,security number, background pattern, reflective fibers, electronicsignal, or other authenticating mark or device from a check. The datainput devices 115 may comprise a device configured to read a magneticstripe from a driver's license, identification card, credit card, orother suitably configured card. The data input devices 115 may comprisea device configured to scan, photograph, or otherwise capture an imageand/or other information from a driver's license or other identificationcard or document. The data input devices 115 may comprise an inputsystem configured to use optical character recognition (OCR) technology.The data input devices 115 may comprise one or more devices or systemsfor obtaining biometric input from the check presenter 101, such as, forexample, a camera, microphone, or device capable of obtaining afingerprint, handprint, voice sample, handwriting sample, iris or retinascan, or other biometric or biomedically implanted information usefulfor identifying the check presenter 101. The data input devices 115 maycomprise a keyboard, keypad, stylus, touchscreen, or other device formanually entering data associated with the proposed check-cashingtransaction. The data input devices 115 may comprise a voice recognitionsystem, or other device for verbally entering data associated with theproposed check-cashing transaction. The data input devices 115 maycomprise a device or system for obtaining other information useful forassessing the risk associated with approving the proposed check-cashingtransaction.

In various embodiments, the check presenter 101 registers with thecheck-cashing entity 110 prior to or at the time of a firstcheck-cashing transaction, providing the check-cashing entity withidentifying information about the check presenter 101 and otherinformation useful for ensuring the security of and/or assessing therisk associated with accepting checks for cashing from the checkpresenter 101. In some embodiments, the check presenter 101 may be askedto provide information about typical checks that the check presenter 101expects to present for cashing. In some embodiments, the check-cashingentity may ask for information about the name and location of theregistering check presenter's 101 employer. For example, the checkpresenter 101 may expect to cash a bi-monthly paycheck from a givenemployer for a given estimated amount of money. In some embodiments, thecheck-cashing entity 110 may ask the check presenter 101 to submit abiometric sample that may be stored and later compared with a biometricsample obtained from the check presenter 101 when a check is beingpresented for cashing. For example, an individual wishing to registerfor check cashing privileges may be asked by the check-cashing entity110 to submit a fingerprint, or to be photographed, or to allow a sampleretina scan to be taken. The biometric sample submitted duringregistration may be stored by the check-cashing entity 110 or by a thirdparty biometric evaluation service and may be used for comparison with asample submitted in association with a proposed transaction.

In some embodiments, when a check presenter 101 is registered for checkcashing and is accepted, the check-cashing entity 110 issues a personalidentification number (PIN) to the check presenter 101 for use insubsequent check-cashing transactions and to allow for easy access tostored information about the check presenter 101. In other embodiments,other useful information is gathered about the check presenter 101and/or about the checks that are expected to be cashed.

In the embodiment shown in FIG. 1, the check-cashing entity 110comprises a communications interface for communicating with the checkauthorization system 100 to request an authorization approval or declinerecommendation for the proposed check-cashing transaction, transmittingat least some of the information received from the check presenter 101and from the check. The check-cashing entity 110 also comprises acommunications interface to receive requests for further informationfrom the check authorization system 100 and to receive an indicationfrom the check authorization system 100 regarding whether to accept orto deny the proposed check-cashing transaction.

In one embodiment, the check authorization system 100 is a businessentity that provides risk assessment services to check-cashing entities110. In one embodiment, the check authorization system 100 is onecomponent of a business entity that that provides check-cashing entities110 with risk assessment services in addition to other check-relatedservices, such as check settlement services, check guarantee services,and the like. In various embodiments, check-cashing entities 110 maycontract with the check authorization system 100 to receive servicescomprising at least one of: validation services, risk assessmentservices, check processing services, and check settlement services.These services may be customized to serve the varying needs andpreferences of different check-cashing entities. For example, riskassessment of proposed check-cashing transactions may be customized,based on a contracted agreement between the check authorization system100 and a given check-cashing entity 110, to accommodate varying levelsof risk tolerance, varying levels of exposure to fraudulentcheck-cashing activities, and varying characteristics of typicaltransactions and typical check presenters on the part of thecheck-cashing entity 110.

In other embodiments, the check authorization system 100 is a softwarecomponent that is internal to the check-cashing entity 10 and thatperforms validation and authorization functions with check-cashingtransactions.

In one embodiment, the check-cashing entity 110 communicates with thecheck authorization system 100 using a dial-up communications medium orother suitable medium for accessing the Internet, which is a globalnetwork of computers. In other embodiments, the check-cashing entity 110communicates with the check authorization system 100 using acommunications medium that may comprise, by way of example, a VirtualPrivate Network (VPN), dedicated communication lines such as T1 or framerelay for host-to-host connection, or other combination of telephonenetworks, wireless data transmission systems, two-way cable systems,customized computer networks, interactive kiosk networks, automaticteller machine networks, interactive television networks, and the like.In other embodiments, the check-cashing entity 110 communicates with thecheck authorization system 100 using other technologies.

As shown in FIG. 1, the check authorization system 100 comprises a datainput component 125, validation routines 135, and a risk scoring anddecisioning component 175. With respect to a variety of differentcomponents associated with the check authorization system 100 anddescribed herein, the components may be embodied as computer programlogic configured to execute on one or more computer processors. In oneembodiment, the program logic may advantageously be implemented as oneor more modules. The modules may comprise, but are not limited to, anyof the following: software or hardware components such asobject-oriented components, class components, task components, processesmethods, functions, attributes, procedures, subroutines, segments ofprogram code, drivers, firmware, microcode, circuitry, data, databases,data structures, tables, arrays, or variables.

The one or more computer processors associated with the checkauthorization system 100 may comprise, by way of example, personalcomputers (PCs), mainframe computers, other processors, program logic,or other substrate configurations representing data and instructions,which operate as described herein. In other embodiments, the processorsmay comprise controller circuitry, processor circuitry, processors,general purpose single-chip or multi-chip microprocessors, digitalsignal processors, embedded microprocessors, microcontrollers and thelike.

In one embodiment, the data input component 125 accepts data that istransferred from the check-cashing entity 110 regarding the checkpresenter 101, regarding the check-cashing entity 110, and regarding thecheck that the check presenter 101 wishes to cash. In some embodiments,the data input component 125 may also receive other data useful forauthorizing a check from other sources. The data input component 125sends the data to the validation routines 135 for validation and for usein risk assessment.

In various embodiments, the validation routines 135 validate the datareceived, as will be described in greater detail with reference to FIG.2. In some embodiments, validating the data comprises verifying thatvarious general characteristics of the data, such as, for example, theformat of the data, the range of the data values, and the like, conformto expected and acceptable specifications. In some embodiments, thevalidation routines 135 serve as a filter, rejecting or returning forcorrection any data that does not conform to the validationspecifications. In some embodiments, validating the data comprisesverifying individual or numerous specific, possibly even unique,characteristics of the data such as, for example, a bar code, checknumber and corresponding dollar amount, watermark, biometricfingerprint, specific known personal identification number (PIN) or ID,or the like.

In some embodiments, the validation routines 135 use the data receivedfrom the check-cashing entity 110 to gather further data that is usefulfor assessing the risk associated with accepting the proposedcheck-cashing transaction. For example, using check accountidentification information and other information that may be gatheredfrom the face of the check, the validation routines 135 may be able toaccess positive pay information for the account, as will be described ingreater detail with reference to FIGS. 5-8. As another example, usingcheck account identification information, the validation routines 135may be able to access stored historical data associated with the accountthat may be indicative of the trustworthiness of the check issuer.

In some embodiments, the validation routines 135 use the data receivedto assign risk scores to various factors associated with the proposedtransaction. In some embodiments, risk scores for variables arecalculated to express a measure of similarity with a desired or expectedvalue. This may be the case when, instead of a perfect match ormismatch, the validation routines indicate similarity or desirability ofsome but not all aspects of a variable. In some embodiments, the factorsare considered as variables in a more comprehensive calculation of riskassociated with proposed transaction and the factor risk scores are usedin a more comprehensive risk scoring calculation or other riskassessment for the proposed transaction.

In the embodiment depicted in FIG. 1, the validation routines 135comprise validation routines for item validation 140, for personvalidation 150, and for location validation 160.

The item validation routines 140 comprise routines for gathering andvalidating data about the check or other financial instrument presentedfor cashing. Item validation routines serve to increase confidence thata financial instrument received for cashing is legitimate, is cashable,and is not a forgery, a stolen check, or a check that has been altered.For example, a MICR validation routine 145 validates that MICRinformation received from the check-cashing entity 110 conforms toaccepted MICR formatting standards. In embodiments where informationabout the check issuer is submitted by the check-cashing entity 110, andwhere such data is available, the MICR validation routine 145 maycomprise routines to verify that the account identified in the MICR lineinformation is indeed associated with the check issuer.

In some embodiments, the item validation routines 140 comprise routinesto access positive pay or other reconciliation information availableabout the check being presented for cashing. Positive pay informationcomprises information made available by a check issuer about checks thatthe check issuer has issued. Other types of reconciliation informationmay be provided by government entities that issue checks and by issuersof traveler's checks, money orders, convenience checks, and the like. Insome embodiments, positive pay information or other reconciliationinformation is used to help assess the legitimacy and cashability of thecheck being presented. Other embodiments use other features and/orcharacteristics of the item to be cashed, comprising, but not limitedto, bar codes, watermarks, special ink bleeds, unique icons, encryptionfeatures, and the like.

Person validation routines 150 comprise one or more routines to gatherand/or evaluate data sent to the check authorization system 100 usefulfor assessing the trustworthiness of the check presenter 101 and forassessing confidence that the check-presenter 101 is the payee of thepresented check. For example, person validation routines 150 maycomprise an identification validation routine 155 that validates anassociation between an identification number received as input and apayee name on the check. In one embodiment, an identification validationroutine 155 verifies that identification information, such as a driver'slicense or social security number, received about the check presenter101 conforms to formatting standards for the type of identification. Inone embodiment, person validation routines 150 comprise routines toevaluate biometric input obtained from the check presenter 101. Personvalidation routines 150 may comprise one or more routines to gatherand/or evaluate other data associated with identifying the checkpresenter 101. For example, person validation routines may also validatefactors that comprise, but are not limited to, personal identificationnumbers (PINs), store or location membership IDs, photo IDs,correspondence of input data, such as name, address, Social SecurityNumber to credit bureau or credit header data, and the like.

Location validation routines 160 comprise routines to collect and/or tovalidate information associated with the check-cashing entity 110. Forexample, a location validation routine 160 may use identificationinformation received about the check-cashing entity 110 to accessadditional information about the check-cashing entity 110 that may berelevant to an assessment of the risk associated with accepting theproposed check-cashing transaction. For example, historical data mayreveal that high-dollar-value checks cashed at pawn shops are morefrequently fraudulent than similar checks cashed at grocery stores, andthis data may be used as a factor in a risk assessment for the proposedtransaction. In embodiments in which information about the proximity ofthe check issuer's location to the check-cashing entity's 110 locationis used for risk assessment, a location validation routine 160 mayaccess information about the location of the check-cashing entity 110for comparison. As another example, the location validation routines 160may additionally or alternatively access information about servicepreferences from a service agreement entered into by the check-cashingentity 110 and the check authorization system 100 that may be relevantto a risk assessment of the proposed transaction. For example,agreements about levels of risk that the check-cashing entity 110 iswilling to accept when cashing a check may influence risk assessment fortransactions at the check-cashing entity 110.

As depicted in the embodiment of FIG. 1, if any of the validationroutines 135 reveal that data received via the data input component 125is not in conformance with expected standards, or otherwise indicates anunacceptable check-cashing transaction, the check authorization system100 may preemptively reject the proposed transaction and may notify thecheck-cashing entity 110 to that effect. In some embodiments, ratherthan preemptively rejecting the proposed transaction, the checkauthorization system 100 may send a request for further information orfor corrected information to the check-cashing entity 110. In otherembodiments, the validation routines 135 may be organized in ahierarchy, such that a set of validations may be performed and passesbefore a next set of validations is performed.

When the validation routines component 135 indicates that the data isacceptable, the check authorization system 100 may activate the riskscoring and decisioning component 175, which in some embodiments,calculates a risk score for the proposed transaction and provides anapproval or decline recommendation to the check-cashing entity 110. Insome embodiments, the validation routines component 135 transmits datathat has been validated as to its format, value range, and the like, andthe risk scoring and decisioning component 175 assigns risk scores tothe risk factors for use in calculating a transaction risk score. Insome embodiments, the validation routines component 135 calculates riskscores associated with individual validated input data items andtransmits the risk scores to the risk scoring and decisioning component17 for use in calculating a risk score for the check-cashingtransaction.

Risk scoring algorithms generally take into account available pieces ofdata that have been determined to be statistically significant to anassessment of the risk associated with accepting a transaction. Thetransaction risk score may be a normalized value that indicates theprobability that the transaction will be good. In some embodiments, riskassessment for the proposed transaction and for the individual riskfactors is accomplished using at least one of: a decision tree, expertsystem, set of business rules, neural network, Bayesian network, or thelike, in addition to or as an alternative to calculating a risk score.Risk scoring and decisioning functions and structures are described ingreater detail with reference to FIGS. 3-4 and FIGS. 8-14.

The check authorization system 100 may be implemented by a businessentity offering services associated with the acceptance and processingof second-party checks. For example, in one embodiment, the checkauthorization system 100 system offers validation services to verify theconformance of data received by the check-cashing entity 110 toacceptable values and/or formats. The check authorization system 100 maybe one component of a more comprehensive business entity that offersservices related to risk management and/or transaction handling forcheck-related or other financial transactions. The check authorizationsystem 100 may also be implemented as computer software, a distributedfile, database accessed via the Internet, or on a computer operated bythe check authorization system 100 or the check-cashing entity 110, oron a server for a networked group of check-cashing entities 110, such asa chain of check-cashing stores, or as a centralized system thatprovides services to entities who subscribe to their services, or insome other suitably configured manner.

Based on service agreements reached between the check-cashing entity 110and the check authorization system 100, a notification based at least inpart on the risk assessment performed by the risk scoring anddecisioning component 175 may be transmitted from the checkauthorization system 100 to the check-cashing entity 110. Thecheck-cashing entity 110 may then accept or decline the check forcashing.

The structure and configuration of components and communications linksdepicted in FIG. 1 are one of a plurality of possible structures andconfigurations suitable to the purposes of the check authorizationsystem 100 described herein. Furthermore, other embodiments of thesystems and methods described herein are envisioned which may comprisesome, all, or none of the features described with reference to FIG. 1.Thus, FIG. 1 is intended to aid in describing and clarifying thefeatures and not to limit the description.

FIG. 2 is a flowchart depicting one embodiment of a process 200 toauthorize the acceptance of second-party checks. The process 200 beginsat a start state and moves to state 205 when a check presenter 101wishing to cash a check or other financial instrument presents theinstrument to a check-cashing entity 110.

The process continues at state 210, where the check-cashing entity 110collects data associated with the proposed check-cashing transaction andsends the data to the check authorization system 100.

In various embodiments, various types of data may be collected by thecheck-cashing entity 110. For example, information about the checkpresenter 101 and information about the check or other financialinstrument to be cashed may be collected and transmitted to the checkauthorization system 100. Some examples of information about the checkpresenter 101 that may, in various embodiments, be collected comprise: adriver's license number, social security number, other identification orPIN number, name, address, employer information, photograph, otherbiometric information, other information from a smart card, informationfrom a biomedical implant, and the like. Some examples of informationabout the check that may be collected comprise: payor information, payeeinformation, check amount, issue date, account number and bank routingnumber for the account on which the check is drawn, other imprintedinformation from the face of the check, MICR line information, opticalor other scan or image of the check or of any authenticating marks orinsignia from the check, information about characteristics of the checksuch as check dimensions and/or reflectivity of the check material, andthe like. In various embodiments, the check-cashing entity 110 maytransmit information about the check-cashing entity 110 itself, so thatthe check authorization system 100 may identify, may categorize, and/ormay access stored information about the check-cashing entity 110, suchas check entity location, type, and/or contracted service parameters.

The check-cashing entity 110 communicates with the check authorizationsystem 100 to request an authorization approval or declinerecommendation for the proposed check-cashing transaction, transmittingat least some of the information received from the check presenter 101and from the check.

The process 200 continues at state 215, where the check authorizationsystem 100 validates the data received from the check-cashing entity110. As was described with reference to FIG. 1, in one embodiment,validation comprises verifying that data received from the check-cashingentity 110 falls into acceptable ranges of values, is correctlyformatted, and makes sense when combined with other data. In otherembodiments, determining that received data is valid may rely on othercriteria. In some embodiments, validating data comprises comparing datainput with stored data values or data ranges. In some embodiments, thecheck authorization system 100 uses internally stored data for comparingwith data input. In some embodiments, the check authorization system 100accesses externally stored data via dial-up or other computercommunication technologies for comparing with data input.

In some embodiments, validation further comprises accessing additionaldata deemed to be useful to a risk assessment of the proposedtransaction. For example, in embodiments that use positive payinformation for calculating a transaction risk score, validation maycomprise accessing stored positive pay information associated with thecheck, as will be described in greater detail with reference to FIGS.5-8. In one embodiment, if positive pay information associated with aproposed transaction indicates a high level of risk associated withaccepting the transaction, the positive pay information may becharacterized as not being “valid” for purposes of approving thetransaction.

The process continues at state 220, where the check authorization system100 determines if the transaction data is valid. In one embodiment, ifsome or all of the data is determined not to be valid, the checkauthorization system 100 notifies the check-cashing entity of theinvalid data in state 225, and in state 255 advises the check-cashingentity 110 not to accept the check for cashing.

Returning to state 220, if the check authorization system 100 determinesthat the transaction data is valid, the process 200 continues in state230, where the risk scoring and decisioning component 175 of the checkauthorization system 100 generates risk scores for some or all of theinput variables as well as a combined risk score for the proposedcheck-cashing transaction, as will be described in greater detail withreference to FIG. 3 and FIG. 4.

Continuing on to state 235, the check authorization system 100 evaluatesthe calculated risk score to determine whether to recommend that thecheck-cashing entity 110 accept or decline the proposed transaction. Inone embodiment, the determination is based on at least one of:predetermined threshold values, pre-agreed business practices associatedwith the entity's 110 service agreement, and business rules affected bythe entity's 110 type. In other embodiments, the check authorizationsystem 100 evaluates the calculated risk score based on other criteria.

The process 200 continues to state 240, where, based at least in part onthe evaluation of state 235, the check authorization system 100recommends accepting or declining the proposed check-cashingtransaction. If the check authorization system 100 determines thatrecommending acceptance of the proposed transaction is indicated, theprocess 200 continues at state 245 where the check authorization system100 advises the check-cashing entity 110 to accept the transaction. Theprocess 200 continues to state 250, where the check-cashing entity 110accepts the check from the check presenter 101 for cashing, and theprocess 200 is complete.

Returning now to state 240, if the check authorization system 100determines that recommending that the check-cashing entity 110 declinethe proposed transaction is indicated, a decline recommendation istransmitted to the check-cashing entity 110. In one embodiment, if arisk score calculated for the transaction falls within a pre-determined“decline range of value” set by the check-cashing entity 110, the checkauthorization system 100 declines or recommends declining the proposedtransaction. The process 200 continues at state 255 where the checkauthorization system 100 advises the check-cashing entity 110 to declinethe transaction. The process 200 continues to state 260, where thecheck-cashing entity 110 may decline to cash the check offered by thecheck presenter 101, and the process 200 is complete.

The flowchart of FIG. 2 describes one embodiment of the process 200 toauthorize the acceptance of second-party checks as comprising variousstates in which various functions are carried out. As will be familiarto one of ordinary skill in the art, in other embodiments, the process200 may be executed using a different order, configuration, or set ofstates, and the states of the process 200 may perform the functionsdifferently from the embodiment of FIG. 2, without departing from thespirit of process 200.

FIG. 3 is a diagram that depicts one embodiment of a set of factors usedto generate a transaction risk score 300 for acceptance of asecond-party check.

Assessing a risk score may advantageously comprise predictive modelingsystems that analyze a plurality of relevant variables, or factors, inorder to determine the probability of a particular transaction beinggood or bad, such as the probability the transaction will or will notclear the banking system. In some embodiments, individual factors or asubset of factors may be evaluated and assigned a risk score, which maythen be used on its own to assess a proposed transactions, or may beaggregated with other scores to generate a transaction risk score.Transaction risk scoring algorithms generally take into account thosepieces of available data that have been determined to be statisticallysignificant to an assessment of the risk associated with accepting atransaction. The risk score may be a normalized value that indicates theprobability that the transaction will be good.

For ease of description, the factors in the embodiment depicted in FIG.3 are illustrated as being conceptually divided into three categories:factors associated with person validation 310, factors associated withlocation validation 320, and factors associated with item validation330. In various embodiments, other categories and/or other factors maybe used additionally or alternatively for use in calculating atransaction risk score 300. Furthermore, the specific instances of itemvalidation, such as using positive pay information, and personalvalidation, such as using biometric information, described herein areintended to be exemplary, rather than limiting.

As was described with reference to validation routines 135 in FIG. 1,person validation refers to a consideration of factors 310 that mayincrease the accuracy of an assessment of the check presenter's 101trustworthiness. Item validation refers to a consideration of factors330 that may increase the accuracy of an assessment of the check item'sauthenticity. Location validation refers to a consideration of factors320 associated with characteristics of the check-cashing entity 110 thatmay provide additional information for increasing the accuracy of a riskassessment for the transaction. In some embodiments, location validation320 further refers to factors reflective of preferences and businessagreements between the check-cashing entity 110 and the checkauthorization system 100.

As depicted in FIG. 3, person validation factors 310 comprise factorsthat serve to identify the check presenter 101, such as, for example,the check presenter's name 312 and identification information 314. Theidentification factors 314 may comprise information from a driver'slicenser or state-issued identification card, other photo identificationcard, a social security card, smart card, transponder, biomedicalidentification implant, or other technology for identifying the checkpresenter 101.

In one embodiment, biometric input 316 obtained from the check presenter101 at the check-cashing entity 110 is used to increase confidence thatthe check presenter 101 is being correctly identified. Examples ofbiometric input include, but are not limited to, input from at least oneof a: fingerprint, palm print, hand geometry, voice sample recognition,facial recognition, facial geometry scan, iris scan, retina scan, DNAsample, biomedical implant chip or other device, signature scan, andkeystroke dynamics. In one embodiment, biometric input information aboutthe check presenter 101 is compared to stored biometric-relatedinformation for the check presenter 101. In one embodiment, biometricinput such as a fingerprint or facial image is input from the checkpresenter 101 at the check-cashing entity 110 and is compared tocorresponding information extracted from another source ofidentification information received from the check presenter 101, suchas a fingerprint or photograph on a driver's license, smart card, orother identification information source. In various embodiments, theabove-described comparisons of biometric input may be executed by thecheck-cashing entity 110, by the check authorization system 100, or by athird party service.

In one embodiment, identification 314 information gathered about thecheck presenter 101 allows the check authorization system 100 to accessstored information about the check presenter's 101 check-related history318. The check-related history 318 may comprise information about checksthat the check presenter 101 has previously written. Thus, for example,if the check presenter 101 has a checking account and has recentlywritten several checks that have bounced, this information may be usedas a factor in an assessment of the risk of accepting the proposedcheck-cashing transaction. The check-related history 318 may compriseinformation about checks that the check presenter 101 has previouslycashed. Thus, for example, if the check presenter 101 has, on a weeklybasis, cashed checks that were settled without problem, this informationmay be used as a factor in an assessment of the risk of accepting theproposed check-cashing transaction. Information about checks that thecheck presenter 101 has cashed may, in some embodiments, be obtained forboth check presenters 101 that have checking accounts and for checkpresenters 101 that do not have checking accounts, thus allowing for anenhanced risk assessment of “unbanked” check presenters 101.

In some embodiments, the check-related history 318 may compriseinformation about the number of check transactions and/or the cumulativedollar amount of the check transactions in which the check presenter 101was recently involved, as will be described in greater detail withreference to FIG. 4. In other embodiments, other types of check-relatedinformation 318 may be used to enhance the risk assessment for aproposed check-cashing transaction. Similarly, in various embodiments,other types of person validation factors 310 may be used to enhance therisk assessment for a proposed check-cashing transaction.

As depicted in FIG. 3, item validation factors 330 comprise factors thatserve to assess a level of confidence in the authenticity andcashability of the check or other financial instrument being presentedfor cashing. Examples of item validation factors 330 used forcalculating a transaction risk score 300, as depicted in FIG. 3,comprise, for example, the amount of the check 332, MICR-lineinformation 334 extracted from the check, and check type 336information. In some embodiments, risk associated with a proposedcheck-cashing transaction may be assessed as being higher with a greatercheck amount 332. MICR-line information 334 may comprise, in someembodiments, information for identifying the bank and the account onwhich the check is drawn, as well as the check number. In someembodiments, information about the check type 332 allows the checkauthorization system 100 to distinguish, for example, a payroll checkfrom a personal check or a cashier's check, which may allow foraccessing associated information and for assessing the proposedtransaction accordingly.

FIG. 3 also depicts the use of check authentication features 340, suchas, for example, a watermark, heat-sensitive mark, security validationnumber, bar code, insignia, background pattern, color scheme,microprinting, colorshifting ink, holographic strips, ultraviolet lightsensitive fibers, encryption, or other authentication mark or devicewhich may serve to enhance confidence in the authenticity of the check,in addition to or as an alternative to features that serve to identify acheck. In some embodiments, a data input device 115 at the check-cashingentity 110 is configured to obtain an image of a bar code, watermark,insignia, or other authenticating mark from the face of the check forcomparison with an expected image of the authenticating mark. In someembodiments, allowances are made for imperfections in data inputtechnology associated with the input device 115 and/or imperfections inthe authenticating mark on the check face that may cause the comparisonwith the expected image of the mark to yield a result that is neither aperfect match nor a definite mismatch. For example, a check that hasbeen folded and refolded before being presented for cashing, or that hasbecome damp, rubbed, or otherwise allowed to experience a degree ofdeterioration, may exhibit an authenticating mark that is less thanperfect even when the check is legitimate and cashable. Aninsignia-related risk score based on a level of confidence associatedwith a comparison of an authenticating mark may be used as a factor in arisk assessment for the proposed transaction.

Also depicted in FIG. 3 as an example of an item validation factor 330is information from a positive pay file 344, other list ofreconciliation information, or check validation information. Positivepay systems are check reconciliation systems whereby a check issuerkeeps a list of issued checks and provides a copy of the list to itsbank or other provider of positive pay information services. The list,often known as a positive pay file, may include information such as, butnot limited to, check identification number, check amount, check issuedate, and payee name. In some embodiments, before the check issuer'sbank accepts a check for debiting from the check issuer's account,information from the presented check is compared to the information onthe positive pay file. If the check does not match an entry on the list,it may not be accepted for cashing or it may be associated with a higherperceived level of risk. As a check is accepted for cashing, a notationmay be made in the positive pay file signifying that the item has nowbeen paid. If the same check, or what appears to be the same check, ispresented again for cashing, the notation in the list shows that thecheck has already been paid, implying that at least one of the checks isa copy or forgery.

Positive pay information may be useful to entities that cashsecond-party checks. Verifying that a check matches information on apositive pay file provided by the check issuer increases thecheck-cashing entity's confidence in the cashability of the check and,thus, in the security of accepting the check.

In other embodiments, as an addition or an alternative to some, all, ornone of the item validation factors described with reference to FIG. 3,other types of factors pertaining to the validity of the item beingpresented for cashing may also be used in calculating a transaction riskscore 300 or in otherwise assessing the risk of the proposedcheck-cashing transaction. As one example, additional reconciliationinformation may be available for issued money orders, traveler's checks,government checks, and the like.

FIG. 3 also depicts examples of location validation factors 320associated with the check-cashing entity 110 that may be used incalculating a transaction risk score 300. Historical trends by industryand location 324 may draw on stored information about previouscheck-cashing transactions at the check-cashing entity 110, or atsimilar check-cashing entities, and upon associated levels of riskassociated with future transactions at similar settings. Thus, if checkscashed at grocery stores have demonstrated a lower level of fraud thanhave checks cashed at gambling casinos, then the historical trends byindustry and location 324 factors of the transaction risk score 300calculation may reflect this information. In some embodiments,check-cashing entities may be categorized according to a StandardIndustry Code (SIC), that may be used to communicate with the checkauthorization system 100 about the check-cashing entity's 110 type andto identify other check-cashing entities of a similar type. In additionor as an alternative to these examples of historical trends by industryand location 324, other types of similar information may be used in thecalculation of the transaction risk score 300.

Check-cashing entity location factors 322 when used in conjunction withinformation from a local businesses database 326 may affect thecalculation and/or evaluation of a geographic-related risk score basedon the proximity of the check-cashing entity 110 to a locationsassociated with an issuer of the presented check. For example, in someembodiments, the risk associated with accepting a check issued by alocal business may be assessed as being lower than the risk associatedwith accepting a check issued by a non-local business. In someembodiments, the risk associated with accepting a check issued by alarge, well-established business may be assessed as being lower than therisk associated with accepting a check issued by a small, newlyestablished business.

Local business databases 326 may be created and/or maintained by thecheck authorization system 100 or by an outside source of information,such as a business or governmental agency. Local business databases 326may comprise information such as, but not limited to, name, address,business type, and business size of businesses in a local area. Forexample, in some embodiments, available census information thatassociates businesses with Metropolitan Statistical Areas (MSA's) inwhich they are located allows the check authorization system 100 toascertain whether a payroll check is written by a business in the sameMSA or in a neighboring MSA to that of the check-cashing entity 110. Thecheck authorization system 100 may have access to one or more localbusiness databases 326 for gaining information useful in assessing therisk associated with accepting a check issued by a given business.

In various embodiments, check-cashing entity location factors 322 maycomprise rules, threshold values, and factor weights pertaining togeographic-related risk assessment that are based on agreementsestablished between the check-cashing entity 110 and the checkauthorization system 100. Using local business databases 326 and otherlocation-related information to enhance risk assessment forcheck-cashing transactions is described in greater detail with referenceto FIGS. 11A, 11B, and 12.

In other embodiments, as an addition or an alternative to some or all ofthe location validation factors 320 described with reference to FIG. 3,other types of factors pertaining to the check-cashing entity 110 may beused in calculating a transaction risk score 300 or in otherwiseassessing the risk of the proposed check-cashing transaction. As oneexample, additional information about known check-issuing governmententities local to the check-cashing entity 110 may be available for usein a risk assessment of the proposed check-cashing transaction.

In other embodiments, factors and/or categories of factors other thanthe person validation 310, location validation 320, and item validation330 factors depicted in FIG. 3, may additionally or alternatively beused to generate a transaction risk score 300 for a proposedcheck-cashing transaction.

FIG. 4 depicts four examples of risk scores that may be calculated forassessing the risk of accepting payroll checks for cashing. For purposesof clarity and ease of explanation, the risk score calculations aredescribed as a simplified set of score calculations for four differenthypothetical transaction situations. In the embodiment depicted in FIG.4, each hypothetical transaction is described in terms of variables 410.Variables 410 are assigned values 420 that may represent a dollaramount, percentage, other numeric amount, category, or the like.Variable values 420 are based at least in part on input obtained inassociation with the transaction. For example, a check amount variable410 may be assigned a value 420 of $1000 based on information receivedfrom the check-cashing entity 110. In the sample score calculationsshown in FIG. 4, the variable values 420 assigned may also be based atleast in part on information associated with the transaction that isaccessed from sources other than the check-cashing entity 110.

As depicted in the sample score calculations of FIG. 4, risk scorefactors, also known as variables 410, are associated with gradated riskscore values 430 that express a level of perceived risk associated withan individual variable value 420. A transaction risk score 440 iscalculated to reflect an assessed level of risk for the transaction as awhole, thus being influenced by the individual risk score values 430. Inthe sample score calculations of FIG. 4, the transaction risk score 440is calculated as the sum of the variable risk scores 430. As will befamiliar to one of ordinary skill in the art, the transaction risk score440 may be calculated according to other methods. As one example, in oneembodiment, variable risk scores 430 are weighted to reflect theirrelevance to a transaction risk assessment before being summed into thetransaction risk score 440.

As described above, the risk score values 430 express a gradated levelof perceived risk associated with the variable values 420. Thus, invarious embodiments, the gradated risk scores allow for an expression ofperceived risk levels that may be other than either an absolute absenceof perceived risk or an absolute absence of perceived security. Invarious embodiments, risk score values 430 may be assigned to variablevalues 420 based on a variety of criteria, business priorities,statistical models, historical observations, and the like. For example,a previously observed pattern of higher risk associated with cashingpayroll checks from small and mid-sized companies over larger companiesmay lead to an assignment of risk scores 430 that reflect higher riskassociated with a paycheck from a company with two hundred and fiftyemployees and lower risk associated with a paycheck from a company withone thousand employees. When variable values 420 are expressed asnumerical values, risk scores 430 may correspond to the variables basedon ranges into which the variable values fall.

In various embodiments, assignments of risk scores to variable valuesmay be customized to suit the preferences and priorities of a givencheck-cashing entity 110 for whom the risk scoring is being carried out.Thus, for example, two check-cashing entities may associate a differentlevel of risk with a given variable value, such as a BiometricConfidence value of 90%, and risk score assignments for the twocheck-cashing entities 110 may be different one from the another.

In some embodiments, risk scores 430 are assigned to variable values 420based on an automated learning or decision-making algorithm thatidentifies risk patterns associated with various variable values 420.For example, the automated learning or decision-making algorithm maycomprise a neural network, Bayesian or other probabilistic network,genetic algorithm, statistical analysis, decision tree, expert system,decision tree, ruled-based decision system, linear calculation, otherscoring mechanism, or a combination of any of the foregoing.

In some embodiments, risk scores 430 are assigned to variable values 420based on a human evaluation of the level of risk associated with variousvariable values 420. In some embodiments, risk scores 430 are assignedto variable values 420 based on a combination of one or more automatedalgorithms and human evaluation. In some embodiments, risk scores 430are assigned to variable values 420 arbitrarily. In some embodiments,methods used to assign risk scores 430 to variable values 420 may vary,based at least in part on trends specific to a given industry or type ofcheck-cashing entity 110. In some embodiments, methods used to assignrisk scores 430 to variable values 420 may vary, based at least in parton preferences expressed by the check-cashing entity 110.

In some embodiments, analysis of check-cashing transactions that allowsfor an observation of risk patterns may be carried out on a regularbasis, such as semi-annually. In some embodiments, variable value/riskscore assignments may be updated accordingly.

In the example depicted in FIG. 4, the four score calculations use thesame set of variables 410. Furthermore, the four score calculations usethe same cutoff value of “235” for the total transaction risk score 440,such that transactions with a total transaction risk score 440 equal toor more than the cutoff value are approved, and transactions with atotal transaction risk score below the cutoff value are denied. In someembodiments that use a transaction scoring system such as thatillustrated in FIG. 4, the cutoff value may be determined based at leastin part on a statistical analysis of past check-cashing transactions andon a level of risk deemed to be acceptable to the check-cashing entity110 and/or to the check authorization system 100. In some embodiments,the cutoff value may be determined by an automated system. In someembodiments, the cutoff value may be determined by a programadministrator or other manager working on behalf of the checkauthorization system 100. In some embodiments, the cutoff value may varyby application, by industry, or by contracted agreements between thecheck-cashing entity 110 and the check authorization system 100.

In other embodiments, other aspects of risk-scoring, such as, but notlimited to: selection of variables 410 to be used in calculating atransaction risk score 440, assignment of values 420 to variables 410,assignment of risk score values 430 to variables 410, and the like, maybe customized to suit the preferences and/or characteristics of acheck-cashing entity 110 or a group of check-cashing entities.

In FIG. 4, the four example Score Calculations A-D assign values 420 forvariables 410 that represent: the value of the check offered forcashing, positive pay information available for the check, informationabout the location and size of the employer/check issuer, a measure ofconfidence based on authentication marks on the check, a measure ofconfidence based on any biometric input associated with the checkpresenter 101, previous known check-writing history of theemployee/check-presenter 101, and a total dollar amount of checktransactions in which the check presenter 101 has been involved duringthe previous six days.

The four example score calculations of FIG. 4 reflect four differentproposed check-cashing transactions, with the variable values 420reflecting various aspects of the proposed transactions. For eachvariable 410 in the score calculations, a score 430 is assigned to thevariable based on the assessed risk associated with the value of thevariable 420. In the examples shown in FIG. 4, a higher score indicatesa higher degree of confidence that the check item will be successfullycashed. For example, the scores for the Check Amount variables in ScoreCalculations A-D assign higher scores to lower Check Amount values, thusreflecting an assumption that the higher the check amount, the greaterthe risk involved in approving the check-cashing transaction. In otherembodiments, Check Amount score values may be assigned to reflect apreferred range of check amounts for cashing or may be based on otherassumptions.

Furthermore, in other embodiments, scores 430 may be assigned tovariables according to other rules and assumptions. For example, higherscores may be assigned to reflect a higher assessment of risk, ratherthan to reflect a lower assessment of risk, as is the case in theexample calculations of FIG. 4. In still other embodiments, transactionsrisk scores may be generated using any one of a number of other methods,as was described in greater detail above, and as will be familiar tothose of ordinary skill in the art.

In these examples, a threshold or cutoff value of “235” points for thetotal transaction risk score 440 is used for determining whichtransactions to approve and which transactions to decline. For example,Score Calculations A and C, with total transaction risk scores 440 of“1050” and “330,” respectively, are approved, while score calculations Band D, with scores of “−820” and “144,” respectively, are declined.

Score Calculation A reflects the hypothetical situation of an employeewith an excellent check-related history who comes to cash a $1000paycheck from a large, local employer, where a search of availablepositive pay information reveals a match between an unpaid item in thepositive pay file and the presented check, where a scan of anauthentication mark on the check provides an excellent match, and whereno biometric input is used. With a transaction risk score of “1050” anda cutoff score of “235,” the transaction is approved.

Score Calculation B reflects the hypothetical situation of anotheremployee with a check-related history that is neither very positive norvery negative who comes to cash a $5000 paycheck from the same large,local employer. In this case, a search of available positive payinformation for the company's paychecks reveals that an item matchingthe presented check has already been paid, and where a scan of anauthentication mark on the check provides a very weak match. As above,no biometric input is used. With a transaction risk score of “−820” anda cutoff score of “235,” the transaction is denied.

Score Calculation C reflects the hypothetical situation of an employeewith a very good check-related history who comes to cash a $100 paycheckfrom an unknown employer, where no positive pay information is availablefor the company's paychecks, and where a scan of an authentication markon the check provides a match with a confidence level of 70%. Biometricinput in this example provides a relatively high degree of confidence inthe check presenter's identity. With a transaction risk score of “330”and a cutoff score of “235,” the transaction is approved.

Score Calculation D reflects the hypothetical situation of an employeewith an average check-related history who comes to cash a $100 paycheckfrom a mid-sized, non-local employer, where a search reveals that, whilepositive pay information is available for the company's paychecks, nomatch with the presented check is found. Furthermore, biometric inputfrom the employee provides an uncertain identification, and where againa scan of an authentication mark on the check provides a match with aconfidence level of 70%. With a transaction risk score of “144” and acutoff score of “235,” the transaction is denied.

Focusing on the use of positive pay information as a factor in riskassessments, the Positive Pay variable scores from Score CalculationsA-D of FIG. 4 illustrate four possible outcomes when positive pay fileinformation is searched in association with a proposed check-cashingtransaction. In Score Calculation A, the check offered for cashingmatches an entry for an unpaid check in the employer's positive payfile, and the high score assigned to the Positive Pay variable reflectsa high degree of confidence in the check's authenticity and cashability.

In one embodiment, in a situation not illustrated in FIG. 4, when apositive pay match is found with regards to a bank number and a checknumber associated with a proposed check-cashing transaction, but whenthe check amount does not match the check amount listed in the positivepay file, a low score, such as “10” may be assigned to the variable toreflect some doubt about the authenticity, correctness, and cashabilityof the presented check.

In Score Calculation B, the check offered for cashing matches an entryfor a previously paid check in the employer's positive pay file,indicating that a problem exists with the check. The check presented bythe employee may be a forgery; the previous check that matched the entrymay have been a forgery; an error may exist in the positive pay file;some other problem may exist. In any event, the very low score assignedto the Positive Pay variable reflects a high degree of doubt about inthe check's authenticity and cashability.

In Score Calculation C, the check offered for cashing does not appear tobe associated with an available positive pay file from the employer. Itmay be that the employer does not use positive pay file technology. Itmay be that the employer provides positive pay information about itspaychecks to a limited set of viewers, but that access to the employer'spositive pay file is unavailable to the check authorization system 100or other entity performing a risk assessment for the transaction. It maybe that an error has caused the positive pay information to incorrectlyappear to be unavailable. Positive Pay information may be unavailablefor another reason, such as a temporary interruption of a computernetwork connection used to access the positive pay information.

In the example shown in Score Calculation C of FIG. 4, the Positive Payvariable is assigned a neutral value that allows the risk scoring anddecisioning component 175 of the check authorization system 100 to avoidpenalizing a check for which no positive pay information is available,while still being able to benefit from the predictive information thatcan be extracted when access to a positive pay file is available.

In Score Calculation D, the check offered for cashing does not match anentry in the employer's positive pay file, although a positive pay filefrom the employer is available, thus indicating that a problem may existwith the check. The check presented by the employee may be a forgery ora stolen check; the employer's positive pay file may not be sufficientlyup-to-date to include an entry for the check; an error may exist in thepositive pay file; some other problem may exist. In any event, the lowscore assigned to the Positive Pay variable reflects a degree of doubtabout the check's authenticity and cashability, while allowing otherrisk variables to overrule the doubt if they are sufficiently positive.In the example in Score Calculation D, the other risk variables are notsufficiently positive to allow for approving the transaction.

Thus, using positive pay information as a factor in a risk assessmentallows a check authorization system 100 or other risk assessment systemto be sufficiently robust to assess a check-cashing transaction evenwhen definitive information as to the cashability of the check is notavailable. The use of positive pay information as a risk assessmentfactor allows a check authorization system 100 to approve cashingchecks, given appropriate mitigating conditions, even when positive payinformation is unavailable or reveals some doubt about the item, whilestill being able to benefit from significant and definitive informationfrom positive pay files when it is available. Systems and methods forusing positive pay information in association with risk scoring for afinancial transaction are described further with reference to FIGS. 5-8below.

Focusing on the use of authentication mark input as a factor in a riskassessment, the insignia-related scores from Score Calculations A-D ofFIG. 4 illustrate several scenarios using authentication mark input inassociation with a risk assessment for a proposed check-cashingtransaction.

Authentication marks are marks or devices associated with a check thatserve to aid in identifying authentic checks. Typically, authenticationmarks are difficult and/or costly for counterfeiters to reproduce andthus help to distinguish authentic from counterfeit checks. Someexamples of authentication marks are: watermarks, bar codes, insignia,color schemes, background patterns, colorshifting ink, holographicstrips, security validation numbers, and ultraviolet light sensitivefibers, among others.

In various embodiments, one or more data input devices 115 at acheck-cashing entity 110 obtain insignia-related information from apresented check.

An insignia-related variable value reflects a measure of similaritybetween the authentication mark or device on the check and an expectedauthentication mark configuration. The expected authenticationconfiguration may be maintained as a stored computer-accessible graphicsor other file, as a stored formula or algorithm, or in some other formuseful for aiding in the assessment of an obtained authentication markor device.

Less than perfect matches between obtained authentication mark data andthe expected authentication mark configuration may be the result of afraudulent check, but may also be the result of such legitimate causesas mechanical limitations of the input device 115, or legitimate wearand tear of the check item.

The sample score calculations reveal a use of authentication mark inputthat goes beyond a rigid, binary, accept/decline judgement based on acomparison of authentication mark input with an expected configurationfor the authentication mark. The score calculations of FIG. 4 illustratean embodiment that integrates the assessment risk based oninsignia-related input into the calculation of a more comprehensivetransaction risk score.

Score Calculations A, B, and D illustrate embodiments in whichinsignia-related scores reflect a level of confidence obtained from aninsignia-related comparison, such as a comparison of a machine-readablewatermark from a presented check with a stored image of an expectedwatermark configuration. In another embodiment, a level of reflectivityexhibited by the fibers of a check material may be captured by an inputdevice 115 at the check-cashing entity 110 and compared with an expectedlevel of reflectivity for the check.

In one embodiment, higher insignia-related values reflect a higher levelof confidence in the accurate authentication of the check and areaccordingly assigned higher scores to reflect an associated higher levelof confidence in the success of the check-cashing transaction, ifapproved. Conversely, low levels of confidence in the accurate matchingof insignia-related input may be assigned low score values to reflect anincreased level of perceived risk associated with approving thecheck-cashing transaction.

Using insignia-related scores that reflect a gradated level ofconfidence in the authenticity of the check presented allows the riskscoring and decisioning component 175 of the check authorization system100 to assess the risk of check-cashing transactions withoutautomatically declining transactions in which the insignia-related levelis below a threshold value. Thus, low insignia-related scores need not,on their own, necessarily disqualify a check-cashing transaction fromapproval, and situations in which low insignia-related scores occur,such as those due to hardware defects, operator errors, physicaldeterioration of the check item caused by normal wear and tear, or otherabnormalities, may be approved.

In FIG. 4, score calculation C depicts a check-cashing transaction inwhich no insignia-related input is obtained from the presented check bythe check-cashing entity 110. Such a situation may occur when acheck-cashing entity 110 is not equipped to obtain insignia-relatedinformation from the checks that it receives for cashing. Such asituation may additionally or alternatively occur when no authenticationmarks or other insignia-related devices are available in associationwith the presented check. In the embodiment shown in Score CalculationC, check presenters 101 with no insignia-related input are assigned amoderate insignia-related score similar to one that may be assigned ifinsignia-related input had been collected and matched with a confidencelevel of 70%. In other embodiments, checks presented at check-cashingentities 110 with no insignia-related input may be handled differently.For example, they may be automatically assigned a higherinsignia-related score, or, in other embodiments, may be automaticallyassigned a lower insignia-related score. In some embodiments,transactions that occur where insignia-related data is not obtained maybe assessed using score calculations that do not includeinsignia-related variables in their calculations, thus avoiding the needto arbitrarily assign an insignia-related score to such transactions.Systems and methods for using insignia-related information inassociation with risk scoring for a financial transaction are describedfurther with reference to FIGS. 13-14 below.

Focusing on the use of biometric input as a factor in a risk assessment,the Biometric Confidence scores from Score Calculations A-D of FIG. 4illustrate several possible uses of biometric input in association witha risk assessment for a proposed check-cashing transaction. The samplescore calculations reveal a use of biometric input that goes beyond abinary, accept/decline judgement based on a comparison of biometricinput and that integrates the assessment risk based on biometric inputinto the calculation of a more comprehensive transaction risk score. Asillustrated in Score Calculations C and D, Biometric Confidence scoresmay be reflective of the level of confidence obtained from a biometriccomparison, such as a comparison of an check presenter's 101 scanneddriver's license photograph with a digital photograph taken of the checkpresenter 101 by the check-cashing entity 110, or a comparison of astored fingerprint image taken during a “registration” transaction witha fingerprint taken by the check-cashing entity 110 at the time of checkpresentment. In one embodiment, higher Biometric Confidence valuesreflect a higher level of confidence in the accurate identification ofthe check presenter 101, and are accordingly assigned higher scores toreflect an associated higher level of confidence in the success of thecheck-cashing transaction, if approved. Conversely, low levels ofconfidence in the accurate matching of biometric input may be assignedlow score values to reflect an increased level of perceived riskassociated with approving the check-cashing transaction. For example, inone embodiment, Biometric Confidence levels that are below 50% may beassigned a negative score value of “−100.”

Using Biometric Confidence scores that reflect a gradated level ofconfidence in the accurate identification of the check presenter 101allows the risk scoring and decisioning component 175 of the checkauthorization system 100 to assess the risk of check-cashingtransactions without automatically declining transactions in which theBiometric Confidence level is below a threshold value. Thus, in someembodiments, situations in which low Biometric Confidence scores occurdue to hardware defects, operator errors, unanticipated physical changeson the part of the check presenter 101, or other abnormalities, may not,on their own, disqualify a check-cashing transaction from approval.

In FIG. 4, Score Calculations A and B depict check-cashing transactionsin which no biometric input is obtained from theemployee/check-presenter 101 by the check-cashing entity 110. Scorecalculations A and B illustrate a scoring policy that exists in someembodiments in which check presenters 101 are not penalized with a lowBiometric Confidence score if the check-cashing entity does not obtainbiometric input. In Score calculations A and B, check presenters 101with no biometric input are assigned a Biometric Confidence scoresimilar to one they would be assigned if biometric input had beencollected and matched with a high degree of confidence. In otherembodiments, check presenters 101 at check-cashing entities 110 with nobiometric input may be handled differently. For example, they may beassigned a Biometric Confidence score reflective of a more moderatelevel of confidence, or may be assigned a Biometric Confidence scorereflective of a low level of confidence. In some embodiments,transactions that occur where biometric data is not collected may beassessed using score calculations that do not include biometricvariables in their calculations. Systems and methods associated with theuse of biometric information for risk scoring of financial transactionsis described further with reference to FIGS. 9-10 below.

Focusing on the use of location-related information as a factor in arisk assessment, Score Calculations A and B in FIG. 4 depict situationsin which the presented checks are written by an employer that has beendetermined to be local, which is reflected in the higher assigned riskscores 430 associated with a higher level of confidence in thetransactions. Score Calculation D depicts a situation in which thepresented check is written by an employer that has been determined to benon-local, which is reflected in the low risk scores 430 associated witha lower level of confidence in the transaction. Score Calculation Cdepicts a situation in which location-related information about theproximity of the check issuer to the check-cashing entity 110 is notavailable. In the embodiment shown in FIG. 4, the mid-rangelocation-related score 430 in Score Calculation C, reflects a policywhich transactions are not penalized when location-related proximityinformation for the check issuer is not available. In variousembodiments, location-related proximity information may be assessed andassigned risk scores differently, as suits the preferences of thecheck-cashing entity 110 and the check authorization system 100, as willbe described in greater detail with reference to FIGS. 11-12 below.

The score calculations depicted in FIG. 4 are intended to illustrate oneembodiment of a method for assigning a risk score 440 to a proposedcheck-cashing transaction and for using the risk score to make arecommendation whether to approve or to deny a proposed check-cashingtransaction. In one embodiment, a score calculation such as thosedepicted in FIG. 4 is created for a given transaction and is printed forreview. With respect to various other embodiments, the scorecalculations of FIG. 4 serve as a symbolic depiction of the type ofcalculation that may be executed to generate an authorizationdetermination for a check-cashing transaction. In still otherembodiments, a consideration of risk factors useful for assessing therisk associated with accepting a proposed check-cashing transaction maybe used in another manner, without departing from the spirit of theinvention described herein.

Risk Scoring Using Positive Pay Information

FIG. 5 shows one embodiment of a database of positive pay information,sometimes known as a positive pay file 500. In the embodiment shown inFIG. 5, the positive pay file 500 is configured as a table of positivepay information, as will be described in greater detail below. In otherembodiments, the positive pay information is stored in one or more otheruseful configurations on a computer-accessible storage medium.

As described above, positive pay information may comprise informationabout checks that have been issued by one or more check issuers, alsoknown in some embodiments as check issuers, check drawers, or payors.The positive pay information may be used to help identify checks thatthe check issuer is willing to honor, that is, is willing to withdrawfunds from an associated accounts for payment of the check. Positive payinformation may be used at least in part to reconcile a record of issuedchecks with a record of paid checks, and thus, in some embodiments,positive pay information may be known as reconciliation information.

In the embodiment shown in FIG. 5, the positive pay file 500 comprisesrecords that correspond to checks written by the check issuer to bedrawn against funds in a given bank account or other source of funds.

In one embodiment, information extracted from the face of the presentedcheck via electronic or magnetic imaging, scanning, optical characterrecognition, manual input or other input technologies is used to accessan associated positive pay record, if one exists. Once an associatedpositive pay record is located for a presented check, information storedin the positive pay file 500 may be compared with information extractedfrom the face of the check and from other sources associated with theproposed check-cashing transaction in order to enhance confidence thatthe presented check is a bona fide, unaltered, cashable check.

In the embodiment depicted in FIG. 5, records in the positive pay file500 comprise at least nine fields. A bank routing number field 509 andbank account number field 510 allow for accurate identification of anaccount associated with a record in the positive pay file 500. A checknumber field 511 stores an identification number for the check or otherfinancial instrument associated with the record. In one embodiment, asearch for positive pay information associated with a check presented toa check-cashing entity 110 identifies the desired positive pay record bylocating a record with a check number field 511 value that matches acheck number encoded in the MICR line of the presented check.

A date issued field 512 stores a record of the date on which theassociated check was written. In some embodiments, the check numberfield 511 and/or the date issued field 512 help to identify a givencheck item when an employer regularly, such as weekly or bi-weekly,issues a check for the same amount to a given employee.

A payee field 513 lists the name of the person to whom the check wasissued, and may be compared to a name obtained from a driver's licenseor other source of identification information available for the checkpresenter 101 and/or may be compared to a payee name on the face of thecheck. In one embodiment, additional identifying information for thepayee is stored in the positive pay file 500. For example, addressinformation for the payee may be stored, an identification number forthe payee may be stored, or any other information that may be used toenhance verification-that the check presenter 101 is the intended payeeof the check.

An amount field 514 stores a record of the amount for which the checkwas written. Comparing the value in the amount field 514 with an amountwritten on the face of the presented check enhances a check-cashingentity's 110 ability to detect checks whose amount information has beenaltered fraudulently.

A payor field 515 stores a record of the company or other entity thatissued the check. In the embodiment shown in FIG. 5, the positive payfile 500 comprises records that correspond to checks written by thecheck issuer against funds in a given bank account or other source offunds. In one embodiment in which the positive pay file 500 storespositive pay information for a company with many divisions, the payorfield 515 may comprise information about the division within the companythat issued the check.

In one embodiment, the positive pay file 500 comprises positive payinformation for a plurality of check issuers' bank accounts. Forexample, a company that manages payroll accounts for and prepares checksfor a number of large businesses may make positive pay information forthe large businesses available to the check authorization system 100. Inembodiments where a positive pay file 500 comprises information for morethan one check issuer, the records of the positive pay file 500 maycomprise a field or fields useful for distinguishing a bank accountand/or check issuer associated with each check. In one embodiment inwhich the positive pay file 500 comprises positive pay informationconsolidated from more than one individual check issuer's positive payfile, the payor field 515 may comprise at least one of: a name of apayor, a bank number and account number of a payor's store of funds, anidentifier for a payor, and an identifier for a payroll or othercheck-writing service contracted by the payor to issue checks on behalfof the payor. Alternately, payor information for the check may be storedusing more than one field in the record. In some embodiments where thepositive pay file 500 comprises information about checks written by onecompany, a payor field 515 may be not needed and not used.

The embodiment of the positive pay file 500 depicted in FIG. 5 furthercomprises a payment/status activity field 516 and a date ofpayment/status activity field 517. In some embodiments, thepayment/status activity field 516 comprises information about activityrelevant to the record that occurs after the check is issued. Examplesof information that may be stored in the payment/status activity field516 comprise, but are not limited to information about: checks cashedand/or otherwise paid, checks voided, stop payments, and checks that areoutstanding and have not yet been paid. In other embodiments, thepayment/status activity field 516 may comprise information about atleast one of: check-cashing transactions in which the check was cashed;check-cashing transactions in which the check was presented for cashing,but was declined; reports of the check being stolen; notification thatthe check has been voided; and notification that a stop-payment has beenplaced on the check. The date of payment/status activity field 517 maycomprise a date associated with activity recorded in the payment/statusactivity field 516.

Thus the payment/status activity field 516 and the date ofpayment/status activity field 517 may serve to store a log of activityassociated with a given check. For example, as described with referenceto Score Calculation B in FIG. 4, the payment/status activity field 516may provide notice to a check-cashing entity 110 or check authorizationsystem 100 that a check with identification features similar to onecurrently being presented for cashing has already been paid by the checkissuer. Conversely, a null value or a value of “active” in thepayment/status activity field 516 for a given check record may providenotice that the check appears to be available for cashing. As anotherexample, in one embodiment, if a check presenter 101 repeatedly presentsa given check at various check-cashing entities 110 for cashing and isrepeatedly declined, the positive pay file 500 may store a record ofthis activity and may provide an alert to suspicious behavior or arecommendation for special attention in handling the check.

As will be familiar to one of ordinary skill in the art, the positivepay file 500 may be configured and may be stored according to any of awide variety of data storage methodologies, without departing from thespirit of the positive pay systems and methods described herein.

FIGS. 6A and 6B are block diagrams of two embodiments of a system thatuses positive pay information to generate a risk score for second-partycheck acceptance. As shown in FIGS. 6A and 6B, a check presenter 101desiring to cash a check provides the check and other associatedinformation to a check-cashing entity 110, as has been described ingreater detail with reference to FIG. 1. The check-cashing entity 110transmits data about the proposed check-cashing transaction to the datainput component 125 of the check authorization system 100. Based onagreements entered into between the check authorization system 100 andthe check-cashing entity 110, the check authorization system 100 mayprovide at least one of: data validation services, data gatheringservices, risk assessment services, guarantee services, and/or checksettlement services for the proposed check-cashing transaction.

As shown in the embodiments of FIGS. 6A and 6B, the data input component125 transmits the received data to the validation routines component 135for validation and for access to additional data relevant to a riskassessment of the proposed transaction. The validation routines 135comprise routines for person validation 150, item validation 140, andlocation validation 160. To reiterate what has been described in greaterdetail with reference to FIG. 1, person validation routines 150 collectand validate data that is considered to be indicative of thetrustworthiness of the check presenter 101; item validation routines 140collect and validate data that is considered to be indicative of theauthenticity of the check item; location validation routines 160 collectand to validate data associated with the check-cashing entity 110.

The validation routines 135 transmit data associated with thetransaction to the risk scoring and decisioning component 175 for riskscoring, or other risk assessment, and for generating an approve/declinerecommendation associated with the proposed transaction to thecheck-cashing entity 110.

As depicted in FIGS. 6A and 6B, the item validation routines 140 accesspositive pay information in order to collect data indicative of thelegitimacy and cashability of the check. FIG. 6A depicts an embodimentin which a positive pay file 500 comprising information associated withthe check is stored by and is made accessible by the check issuer 600 orby another entity operating on behalf of the check issuer 600. Forexample, an employer who is the issuer of a payroll check may authorizeits bank, a payroll service, or another positive pay service entity tomaintain and to provide access to positive pay information associatedwith its payroll checks. Similarly, an issuer of insurance refund checksmay provide access to information associated with its insurance refundchecks.

In various embodiments, the item validation routines 140 of FIG. 6Aaccess the positive pay file 500, which may be stored at a financialentity, via a communications system. Examples of appropriatecommunications systems comprise, but are not limited to, wired orwireless computer network systems, telephone systems, dedicatedconnections, and the like. In other embodiments, the item validationroutines 140 access the positive pay file 500 using a communicationsmedium that may comprise, by way of example, a dial-up communicationssystem, a Virtual Private Network (VPN), dedicated communication linessuch as T1 or frame relay for host-to-host connection, or othercombination of telephone networks, wireless data transmission systems,two-way cable systems, customized computer networks, interactive kiosknetworks, automatic teller machine networks, interactive televisionnetworks, and the like. In other embodiments, the check-cashing entity110 communicates with the check authorization system 100 using othertechnologies.

FIG. 6B depicts an embodiment in which a positive pay file 500comprising information associated with the check is transmitted by thecheck issuer 600 or by another entity operating on behalf of the checkissuer 600 to the check authorization system 500 for internal storage.For example, a payroll service acting on behalf of a check issuer 600may daily transmit, download, or update a positive pay file 500 for useby the item validation routines 140 of the check authorization system100.

FIGS. 7A and 7B are block diagrams of two embodiments of a system foraccessing positive pay information using a positive pay routing table720. FIG. 7A depicts an embodiment of a system to access externallystored positive pay information. FIG. 7B is a block diagram of oneembodiment of a system to access internally stored positive payinformation. Both the embodiment depicted in FIG. 7A and the embodimentdepicted in FIG. 7B may be implemented in conjunction with theembodiment of the check authorization system 100 depicted in FIGS. 6Aand 6B. Furthermore, the check authorization system 100 may implement anembodiment of the system to access positive pay information thatcomprises elements of the embodiments depicted in FIGS. 7A and 7B.

Additionally or alternatively, the embodiments depicted in FIGS. 7A and7B may be implemented in conjunction with systems 700 that accesspositive pay information for use associated with check-cashingtransactions, but that do not provide the validation and/or riskassessment services offered by the check authorization system. Thus, theterm check authentication system 700 is used in FIGS. 7A and 7B. Invarious embodiments of the check authorization system 100, positive payinformation is accessed using a positive pay routing table 720 as isdescribed in FIGS. 7A and 7B.

Referring now to FIG. 7A, a check presenter 101 presents a check to acheck-cashing entity 110 for cashing. The check-cashing entity 110communicates with a check authentication system 700 that provides accessto positive pay information for the check. Data sent by thecheck-cashing entity 110 is received by the check authentication system700 via a data interface 710. In one embodiment, the data comprises atleast one of: a bank routing number and bank account number, a checkissue date, a check number, an amount, a payee name, and a payor name.The data may additionally or alternatively comprise other informationuseful for locating positive pay information for the check. Datacollected from the check may be obtained using at least one of a varietyof technologies, comprising but not limited to: digital scanning,optical character recognition, MICR scanning, and manual input based onvisual inspection.

In the embodiment shown in FIG. 7A, check issuers 600 may compriseemployers or other businesses that issue checks, payroll services thatmanage payroll accounts for employers, banks that manage payrollsaccounts or other checking accounts for businesses, third party servicesthat provide positive pay information, or the like. As shown in FIG. 7A,check issuers 600 maintain positive pay files 500 that store informationabout issued checks, as was described in greater detail with referenceto FIG. 5. The check authentication system 700 uses the data receivedvia the data interface 710 to access an associated record in thepositive pay routing table 720. The embodiment of the positive payrouting table 720 depicted in FIG. 7A provides information that allowsthe check authentication system 700 to access an externally storedpositive pay file 500 associated with the check.

As depicted in FIG. 7A, the records of the positive pay routing table720 may comprise two fields for identifying a positive pay file 500associated with the presented check. In other embodiments, the fieldsused for determining which of a plurality of positive pay files toaccess may be at least one of the set consisting of: bank routingnumber, bank account number, subscriber number or name and check issuer.In other embodiments, other fields may be used to identify a positivepay file with a presented negotiable instrument and to provide accessinformation for the identified positive pay file 500. In one embodiment,using information received by the data interface 710, the checkauthentication system 700 identifies a check issuer 600 that maintainsthe associated positive pay file 500.

The check authentication system 700 accesses the positive pay file 500,and, using the data received from the check-cashing entity 110, accessesa record associated with the check, if one exists. In some embodiments,this positive pay data may then be “scored” using customizable rules androutines in order to generate a positive pay score, as will be describedin greater detail below.

The positive pay score may then be aggregated with other variable scoresas was exemplified in the score calculations of FIG. 4 to calculate atransaction score. In some embodiments, the transaction score may thenbe assessed in order to determine if it is within a pre-set range ofacceptable scores that is customizable based on a tolerance for risk setby the check authorization system 100 and/or by the check-cashing entity110. As will be described in greater detail with reference to FIG. 8below, the check authentication system 700 may transmit informationobtained from the positive pay file 500 about the check or anaccept/decline recommendation based at least in part on informationobtained from the positive pay file 500 about the check to thecheck-cashing entity 110 via the data interface 710. The check-cashingentity may then decide whether to accept the proposed check-cashingtransaction based at least in part on the positive pay informationreceived from the check authentication system 700.

Referring now to FIG. 7B, a check presenter 101 presents a check to acheck-cashing entity 110 for cashing. The check-cashing entity 110communicates with a check authentication system 700 that provides accessto positive pay information for the check. Data sent by thecheck-cashing entity 110 is received by the check authentication system700 via a data interface 710. In one embodiment, the data comprises atleast one of: a bank account number and bank routing number, a checkissue date, a check number, an amount, a payor name, a payee name, and apayee identifier, such as a driver's license number, a Social Securitynumber, a government issued identification number, and the like. Thedata may additionally or alternatively comprise other information usefulfor locating positive pay information for the check. Data obtained fromthe check may be obtained using at least one of a variety oftechnologies, comprising but not limited to: digital scanning, opticalcharacter recognition, MICR scanning, and manual input based on visualinspection.

In the embodiment shown in FIG. 7B, check issuers 600 may compriseemployers or other businesses that issue checks, payroll services thatmanage payroll accounts for employers, banks that manage payrollsaccounts or other checking accounts for businesses, third party servicesthat provide positive pay information, or the like. As shown in FIG. 7B,check issuers 600 provide their positive pay files 500 to the checkauthentication system 700 for internal storage. The positive pay files500 may be updated regularly, intermittently, or as suits thepreferences of the check authentication system 700 and the check issuer600.

The check authentication system 700 may store separate positive payfiles 500 internally for individual check issuers 600, as depicted inFIG. 7B. In other embodiments, the check authentication system 700 mayjoin more than one positive pay file 500 received from one or more checkissuers 600 into an expanded positive pay file 500.

The check authentication system 700 uses the data received by the datainterface 710 to access an associated record in the positive pay routingtable 720. The embodiment of the positive pay, routing table 720depicted in FIG. 7B provides information that allows the checkauthentication system 700 to access an internally stored positive payfile 500 associated with the check.

As depicted in FIG. 7B, the records of the positive pay routing table720 comprise two fields: a field that identifies a bank routing and/oraccount number and a field that provides access information for anassociated positive pay file. Using information about an account numberreceived by the data interface 710, the check authentication system 700identifies an associated, internally stored positive pay file 500. Inother embodiments, the records of the positive pay routing table 720comprise several fields. The fields used for determining which positivepay file to access may be, for example, bank routing number, bankaccount number, payee name or other identifier, and/or check issueridentification.

The check authentication system 700 accesses the internal positive payfile 500, and, using the data received from the check-cashing entity110, accesses a record associated with the check, if one exists. As willbe described in greater detail with reference to FIG. 8 below, the checkauthentication system 700 transmits information obtained from thepositive pay file 500 about the check to the check-cashing entity 110via the data interface 710. The check-cashing entity may then decidewhether to accept the proposed check-cashing transaction based at leastin part on the positive pay information received from the checkauthentication system 700. In some embodiments, the check authenticationsystem 700 may generate a positive pay risk score based at least in parton information accessed in the positive pay file 500, as was describedin greater detail with reference to FIG. 7A, and may transmit the scoreto the check-cashing entity 110.

FIGS. 7A and 7B depict embodiments in which the positive pay routingtable 720 provides access information for positive pay files 500 thatare stored either externally or internally to the check authenticationsystem 700, respectively. In other embodiments, at least one checkissuer 600 may choose to maintain its positive pay file 500 externallyto the check authentication system 700, at least one check issuer maychoose to provide its positive pay file 500 to the check authenticationsystem 700 for internal storage, and the positive pay routing table 720may provide routing information for accessing both internally andexternally stored positive pay files 500.

Furthermore, FIGS. 7A and 7B depict embodiments in which checks issuedfrom a given bank account are associated with a single positive pay file500. In other embodiments, checks issued from a given bank account or bya given check issuer 600 may be associated with a plurality of positivepay files 500, and the positive pay routing table 720 may be configuredto provide access to one or more of the plurality of positive pay files500. For example, an employer may make positive pay information aboutissued payroll checks available from a positive pay file 500 accessibleby the check authentication system 700, while a third party positive payinformation service provider may also make a copy of the informationavailable to the check authentication system 700. As will be familiar toone of ordinary skill in the art, such embodiments may be implementedwithout departing from the spirit of the systems and methods describedherein.

FIG. 8 is a flowchart that depicts one embodiment of a process 800 touse positive pay information as a factor in a risk-scoring calculationfor second-party check acceptance. The process 800, as depicted in FIG.8, begins at a start state and moves to state 810 where the data inputcomponent 125 of the check authorization system 100 receives input abouta proposed check-cashing transaction from a check-cashing entity 110.

Moving on to state 820, the input is transmitted to the validationroutines 135, where the input useful for locating positive payinformation is identified and, in state 830, is used to locateinformation associated with the presented check in a positive pay file500. Input useful for locating positive pay information may compriseinformation extracted electronically, magnetically, or visually from theface of the presented check. In one embodiment, input useful forlocating positive pay information may be transformed into a commonformat and may be input into the check authentication system 700. Forexample, in one embodiment, input related to positive pay may compriseat least one of: bank routing and account number, check number, payor,payee, payee identifier, check amount, and check issue date. In oneembodiment, input related to positive pay information may comprise otherinformation gathered from the check presenter 101. In one embodiment,the item validation routines 140 of the check authorization system 100use the input to locate a positive pay file 500 with information aboutchecks issued by the payor of the presented check.

Moving on to state 840, the item validation routines 140 of the checkauthorization system 100 use the input to attempt to locate a record inthe identified positive pay file 500 that is associated with thepresented check.

Moving on to state 850, the item validation routines 140 compare datafrom the fields 511-517 of the associated positive pay file record, ifone was located, to data about the presented check that was receivedfrom the check-cashing entity 110. In some embodiments, the itemvalidation routines 140 note whether some, all, or none of the fields511-517 of the record match associated information from the presentedcheck. In some embodiments, the item validation routines 140 assign apositive pay category to the check-cashing transaction based on acomparison of the presented check and the positive pay record, as wasexemplified with reference to the score calculations of FIG. 4.

For example, in one embodiment, if information from the presented checkmatches associated fields in the positive pay record and if the recordindicates that the check has not yet been cashed, the check-cashingtransaction may be assigned a category of MATCH, indicating a highlikelihood that the check is legitimate. In another embodiment, thecheck-cashing transaction may be assigned a score or value indicatinghigh confidence, which further indicates a high likelihood that thecheck is legitimate.

In one embodiment, if the bank number and check number on the presentedcheck match those in a positive pay record, but the check amount doesnot match, the transaction may be assigned a category of PARTIAL MATCH.In another embodiment, the transaction may be assigned a score or valueindicating less confidence, which further indicates a lesser chance,when compared to the former example, that the check is legitimate.Additionally, the system may send the variance between the check amountin the positive pay file and the check being presented for cashing tothe risk scoring decisioning component 175 to assign a score or valuebased on rules created for deviation between amounts. For example, adeviation of a few cents or a few whole dollars, such as $107 vs. $108,may be attributed to mis-keying of amount at the check-cashing entity110 and may yield one score indicative of lower risk as compared to anamount that differs by total number of digits, such as $1,000 vs. $100,which may yield a different score.

If information from the presented check matches the associated fields inthe positive pay record and if the record indicates that the check hasalready been cashed, the check-cashing transaction may be assigned acategory of ITEM PAID, indicating a high likelihood that the check is acopy or is otherwise fraudulent or that the paid check was fraudulent.Similarly, a transaction may be assigned a category of ITEM STOPPED orITEM VOIDED in situations where the check has been stopped or voided,respectively.

Based on proprietary rules that may be customized to suit thepreferences of individual or groups of check-cashing entities, theassignment of an ITEM PAID, ITEM STOPPED, or ITEM VOIDED category or anequivalent scoring method may yield a positive pay risk score thatfurther aggregates into the transaction risk score and that determineswhether this transaction will be approved or declined, based onagreements made between the check-cashing entity 110 and the checkauthorization system 100.

If a positive pay file 500 with information about checks issued by thepayor is available, but no record exists within the positive pay file500 that matches the information from the presented check, then thetransaction may be assigned a category of NO MATCH. A transactionassigned to a NO MATCH category may occur legitimately when the recordsin a positive pay file 500 are not sufficiently up-to-date to reflectrecently issued checks. A NO MATCH category may also reflect thepossibility that the check is fraudulent, or may reflect anothersituation. Based on proprietary rules that may be customized to suit thepreferences of individual or groups of check-cashing entities, theassignment of a NO MATCH category or an equivalent scoring method mayyield a positive pay risk score that further aggregates into thetransaction risk score and that determines whether this transaction isto be approved or declined, based on agreements made between thecheck-cashing entity 110 and the check authorization system 100.

If a positive pay file 500 with information about checks issued by thepayor is not available, the transaction may be assigned a category ofDATA UNAVAIL, which may occur when the payor does not offer positive payinformation or when the check authorization system 100 does not haveaccess to the payor's positive pay information. Based on proprietaryrules that may be customized to suit the preferences of individual orgroups of check-cashing entities, the assignment of a DATA UNAVAILcategory or an equivalent scoring method may yield a positive pay riskscore that further aggregates into the transaction risk score and thatdetermines whether this transaction is to be approved or declined, basedon agreements made between the check-cashing entity 110 and the checkauthorization system 100.

In other embodiments, a different set of positive pay categories may beused to indicate whether or not a presented check item appears to be avalid item based on information from the positive pay file 500. In yetother embodiments of the process 800, a comparison of information fromthe presented check and information from the positive pay file 500directly generates a positive pay risk score value, as will be describedwith reference to the description of state 860, without first beingassigned a positive pay risk category.

Furthermore, in some embodiments, more than one positive pay file 500may be accessed in association with a presented check. In someembodiments, a positive pay risk category may be assigned for eachaccessed positive pay file 500. In some embodiments, a positive pay riskcategory based on a collective assessment of information obtained from aplurality of positive pay files 500 may be determined for thetransaction. In other embodiments, information from a plurality ofpositive pay files 500 may be assessed in other manners and the positivepay risk score determined for the proposed check-cashing transaction.

In other embodiments, the item validation routines 140 may characterizea comparison of the presented check and the positive pay record in termsof a percentage or other numeric score. In yet other embodiments, anassessment of a comparison between the presented check and the positivepay record may be carried out by the risk scoring and decisioningcomponent 175 or by another component of the check authorization system100.

Moving on to state 860, the item validation routines 140 transmit theassigned positive pay category to the risk scoring and decisioningcomponent 175 of the check authorization system 100, where the riskscoring and decisioning component 175 assigns a positive pay risk scoreto the transaction based at least in part on the positive pay category.

As was described in greater detail with reference to FIG. 4, theassigned positive pay risk score reflects a perceived level of riskassociated with approving a transaction with the assigned positive paycategory. For example, in one embodiment, a positive pay category ofMATCH is assigned a risk score of “500”; a positive pay category ofPARTIAL MATCH is assigned a risk score of “10”; a positive pay categoryof NO MATCH is assigned a risk score of “−100”; a positive pay categoryof ITEM PAID, ITEM STOPPED, or ITEM VOIDED is assigned a risk score of“−1000”; and a positive pay category of DATA UNAVAIL is assigned a riskscore of “50”. In other embodiments, risk scores may be assigned totransactions according to other criteria.

Additionally, in other embodiments, there may be more than one variationof a partial match with information in the positive pay file 500,wherein the variations of partial match may each have a unique score,which may vary by type of check-cashing entity 110. In some embodiments,the positive pay risk score is used alone to assess the risk of atransaction. In other embodiments, the positive pay risk score is usedas one factor in the calculation of a transaction risk score. In someembodiments, the positive pay risk score and/or the transaction scoremay be interpreted within the framework of a score card or set ofpreference-based agreements that identify acceptable and unacceptableranges of scores and that determine what transactions are approved anddeclined.

As was described with reference to FIG. 1, in some embodiments, the itemvalidation routines 160 may assign the positive pay risk score to thetransaction and may transmit the assigned score along with otherinformation about the transaction to the risk scoring and decisioningcomponent 175 for scoring and an approve/decline recommendation.

As was described in greater detail with reference to FIG. 4 above, thepositive pay risk score expresses a gradated level of perceived riskassociated with the positive pay category or other positive pay variablevalue 420. In various embodiments, a gradated positive pay risk scoremay be assigned to positive pay variable values 420 based on a varietyof criteria, business priorities, statistical models, historicalobservations, and the like. In some embodiments, positive pay riskscores are assigned to positive pay variable values 420 based on anautomated learning or decision-making algorithm that identifies riskpatterns associated with various variable values 420. In someembodiments, positive pay risk scores are assigned to positive payvariable values 420 based on a human evaluation of the level of riskassociated with various variable values 420. In some embodiments,positive pay risk scores are assigned to positive pay variable values420 based on a combination of one or more automated algorithms and humanevaluation. In some embodiments, positive pay risk scores are assignedto positive pay variable values 420 arbitrarily. In some embodiments,methods used to assign positive pay risk scores to positive pay variablevalues 420 may vary, based at least in part on trends specific to agiven industry or type of check-cashing entity 110. In some embodiments,methods used to assign positive pay risk scores to positive pay variablevalues 420 may vary, based at least in part on preferences expressed bythe check-cashing entity 110.

Moving on to state 870, the risk scoring and decisioning component 175,in one embodiment, integrates the assigned positive pay score with othervariable risk scores 430 that reflect risk associated with other aspectsof the proposed check-cashing transaction, such as, for example, thecheck amount, the check-related history of the check presenter 101, andinformation about the check issuer, as was exemplified with reference tothe score calculations of FIG. 4. Based at least in part on the positivepay risk score, the risk scoring and decisioning component 175calculates a transaction risk score 440 for the proposed transaction.

Moving on to the end state, the process 800 to use positive payinformation as a factor in a risk scoring calculation for acheck-cashing transaction is complete. In one embodiment, the process800 to use positive pay information as a factor in a risk score is usedas part of a larger risk assessment process, in which the risk scoringand decisioning component 175 transmits a recommendation to approve orto decline the proposed check-cashing transaction to the check-cashingentity 110, based at least in part on the transaction risk score 440calculated by the process 800.

As was described in greater detail with reference to FIG. 4, thetransaction risk score 440 may, in some embodiments, be calculated asthe sum of the variable risk scores 430. In other embodiments, thetransaction risk score 440 may be calculated according to other methods.As one example, the variable risk scores 430 may be weighted to reflecttheir relevance to a transaction risk assessment before being summedinto the transaction risk score 440.

Furthermore, recommendations based at least in part on transaction riskscores may be influenced by preferences, business decisions, andagreements set by the check-cashing entity 110, such that the sametransaction risk score could lead to a recommendation to approve acheck-cashing transaction for one check-cashing entity 110 and couldlead to a recommendation to decline a check-cashing transaction foranother check-cashing entity 110.

The flowchart of FIG. 8 describes one embodiment of the process 800 forusing positive pay information to generate a risk score for second-partycheck acceptance as comprising various states in which various functionsare carried out. As will be familiar to one of ordinary skill in theart, in other embodiments, the process 800 may be executed using adifferent order, configuration, or set of states, and the states of theprocess 800 may perform the functions differently from the embodiment ofFIG. 8, without departing from the spirit of process 800.

Risk Scoring Using Biometric Information

FIGS. 9A, 9B, 9C, and 9D are block diagrams depicting four embodimentsof a system that uses biometric input to generate a transaction riskscore for second-party check acceptance. Examples of biometric inputcomprise, but are not limited to, input from: fingerprint, palm print,hand geometry, voice sample recognition, facial recognition, facialgeometry scan, iris scan, retina scan, DNA, signature scan, andkeystroke dynamics. Biometric input obtained from the check presenter101 by the check-cashing entity 110 may be compared to biometricinformation available from a known person, as will be described ingreater detail below. Biometric information may thus be used to enhanceconfidence in the accurate identification of the check presenter 101 andmay enhance confidence that the check presenter 101 is the correct payeeof the presented check. By incorporating biometric input in a riskscoring system for check cashing, an assessment of the check presenter'sidentity may be considered along with other factors indicative of alevel of security associated with a proposed check-cashing transaction.

In the embodiments shown in FIGS. 9A, 9B, 9C, and 9D, biometric inputfrom the check presenter may be obtained by the check-cashing entity 110using a biometric input device 910. Biometric devices 910 may be of avariety of biometric input devices, commercially available currentlyand/or in the future, that measure, scan, image, record, or the likefrom the check presenter 101 to generate a biometric input.

In the embodiments shown in FIGS. 9A, 9B, 9C, and 9D, the biometricinput received from the input device 910 is evaluated by a biometricinput evaluator 920. The biometric input evaluator 920 compares theinput from the biometric input device 910 with other available biometricinformation from the person who the check presenter 101 is claiming tobe, thereby enhancing confidence in the correct identification of thecheck presenter 101. In the case of a second-party check transaction,the check presenter 101 is typically claiming to be to the payee of thecheck. When biometric input obtained from the check presenter 101 iscompared to biometric information available for the payee of thepresented check, the biometric input evaluator 920 may generate a rawscore that expresses a level of similarity between the two and that mayexpress a gradated level of confidence that the check presenter and thepayee are the same person. In some embodiments, the raw score isexpressed as a percentage of total confidence or similarity. In someembodiments, the raw score is expressed in another form, such as onethat uses a system of categorization for expressing levels of confidencein the identity of the check presenter 101.

In the embodiments depicted in FIGS. 9A and 9B, biometric input such asa fingerprint or facial image received from the check presenter 101 atthe check-cashing entity 110 may be compared by the biometric inputevaluator 920 to corresponding information extracted from another sourceof identification information received from the check presenter 101during the check-cashing transaction. For example, in one embodiment,biometric input obtained from the check presenter 101 at the time ofcheck presentment may be compared to a fingerprint, a photograph, orother additional biometric information available on a driver's license,smart card, or other identification information source that is providedby the check presenter 101 to the check-cashing entity 110.

In the embodiments depicted in FIGS. 9C and 9D, biometric inputinformation received from the check presenter 101 during thecheck-cashing transaction is compared by the biometric input evaluator920 to stored biometric-related information. In some embodiments,individuals who wish to use the services of the check-cashing entity 10may first register prior to having a check to cash, establishing theiridentity with the check-cashing entity 110 by having a photograph,fingerprint, or other biometric identification sample taken and storedfor future comparisons by the biometric input evaluator 920. Storedbiometric information provided at a registration transaction may bestored for future comparisons by the check-cashing entity 110, by thecheck authorization system 100, and/or by a third party biometricevaluation service, as will be described in greater detail below.

In other embodiments, the biometric input evaluator 920 may use anothersource of stored biometric information, such as a government database offingerprints or an employer-supplied repository of employee photographsfor comparison with the biometric input information received from thecheck presenter 101 during the check-cashing transaction. Such storedbiometric information may be maintained for future comparisons by thecheck-cashing entity 110, by the check authorization system 100, and/orby a third party biometric evaluation service, as will be described ingreater detail below.

Describing FIGS. 9A, 9B, 9C, and 9D individually now:

In FIG. 9A, the check presenter 101 presents a check to a check-cashingentity 110. The check-cashing entity 110 obtains various types ofinformation associated with the proposed check-cashing transaction fromthe check presenter 101, as was described in greater detail withreference to FIG. 1. In the embodiment shown in FIG. 9A, thecheck-cashing entity 10 comprises a biometric input generator 900. Thebiometric input generator 900 comprises the biometric input device 910,which receives the biometric input from the check presenter 101, and theinput evaluator 920, which compares the biometric input from the inputdevice 910 to other information received from the check presenter 01 atthe check-cashing entity location 110. For example, the biometric inputdevice 910 may be a camera that photographs the check presenter's 101face, and the input evaluator 920 may be a component configured tocompare the photograph with a scanned image of the check presenter's 101driver's license photograph, received from the check presenter 101 inconjunction with the proposed transaction. Alternatively, the inputevaluator 920 may be a component configured to compare the photographwith a scanned image of the check presenter 101 that was taken when thecheck presenter 101 was previously registered with the check-cashingentity 110 and that has been stored for comparison.

In the embodiment depicted in FIG. 9A, the input evaluator 920 generatesa raw numeric Biometric Confidence score or other expression of a levelof confidence that the biometric input matches the other availablebiometric information received from the check presenter 101. In oneembodiment, the Biometric Confidence score is expressed as a percentageor probability that two pieces of biometric data identify the sameperson. Thus, a score of 100% may expresses a high level of confidencethat the check presenter 101 is the same person described by the otherbiometric information. A score of 50% may express confidence that thereis a 50% probability that the check presenter 101 is not the same personas described by the other biometric information. In other embodimentsthe Biometric Confidence is expressed as a more general numeric value orscore.

The check-cashing entity 110 transmits the Biometric Confidence scoregenerated by the biometric input evaluator 900 to the data inputcomponent 125 of the check authorization system 100 together with othertypes of information associated with the proposed check-cashingtransaction.

The data input component 125 transmits the received input to thevalidation routines 135 for item validation 140, person validation 150,and location validation 160. In some embodiments, the person validationroutines 150 generate a Biometric Confidence score, also known as abiometric risk score, based at least in part on the raw numeric score.The Biometric Confidence score may be generated based on specific orproprietary rules for interpreting the comparison of the initial orregistered biometric input, with the current transaction input. Further,these rules may yield the same or different scores based on similarinput. For example, in accordance with the preferences of somecheck-cashing entities 110, or with respect to some industries orlocations, a given partial match may yield a score of “40”, but inaccordance with the preferences of other check-cashing entities 110, itcould yield a score of “30.”

From the validation routines 135, the input data is transmitted on tothe risk scoring and decisioning component 175, where a transaction riskscore is calculated, based at least in part on the biometric input, andan approve/decline recommendation formulated for the proposedcheck-cashing transaction, as was described in greater detail withreference to FIGS. 1, 3, and 4.

In other embodiments, biometric input obtained from the check presenter101 at the time of check presentment is compared to previously storedbiometric information for the individual,

Moving on now to a description of FIG. 9B, the check presenter 101presents a check for cashing to a check-cashing entity 110. Thecheck-cashing entity 110 obtains from the check presenter 101 varioustypes of information associated with the proposed check-cashingtransaction, as was described in greater detail with reference toFIG. 1. In the embodiment shown in FIG. 9B, the check-cashing entity 110comprises a biometric input device 910, which receives the biometricinput from the check presenter 101.

The check-cashing entity 110 transmits the biometric input to the datainput component 125 of the check authorization system 100 together withother types of information associated with the proposed check-cashingtransaction. In the embodiment shown in FIG. 9B, the input from thebiometric input device 910 is transmitted to the check authorizationsystem 100 before the input is compared and/or evaluated. Similarly, theother biometric information is transmitted to the check authorizationsystem 100 prior to comparison. Instead, comparison of the biometricinput and the other biometric information is carried out by the checkauthorization system 100, as will be described in greater detail below.

The data input component 125 transmits at least some of the receivedinput to the validation routines 135 for item validation 140, personvalidation 150, and location validation 160.

In the embodiment depicted in FIG. 9B, the check authorization system100 further comprises the biometric input evaluator 920. The data inputcomponent 125 is configured to transmit to the biometric input evaluator920 both the biometric input obtained using the biometric input device910 and the other biometric information received from the checkpresenter 101, as was described in greater detail with reference to FIG.9A. The input evaluator 920 compares the biometric input from the inputdevice 910 to the other biometric information received from the checkpresenter 101 and generates a raw numeric Biometric Confidence score orother expression of a level of confidence that the biometric inputmatches the other available biometric information received from thecheck presenter 101. The biometric input evaluator 920 transmits theBiometric Confidence score or other measure to the person validationroutines 150, for inclusion with other validated data from thevalidation routines 135.

As was described with reference to FIG. 9A, in some embodiments, theperson validation routines 150 generate a biometric risk score, based atleast in part on the raw numeric score. The biometric risk score may begenerated based on specific or proprietary rules for interpreting thecomparison of the initial or registered biometric input, with thecurrent transaction input. Further, these rules may yield the same ordifferent scores based on similar input.

From the validation routines 135, the validated data is transmitted tothe risk scoring and decisioning component 175, where a transaction riskscore is calculated, based at least in part on the biometric input, andan approve/decline recommendation is generated for the proposedcheck-cashing transaction, as was described in greater detail withreference to FIGS. 1, 3, and 4.

In the embodiments depicted in FIG. 9C, the biometric input evaluator920 evaluates the biometric input by comparing the input to storedbiometric information about the person to whom the check is issuedrather than to additional information gathered from the check presenter101 by the check-cashing entity 110. For example, a fingerprint obtainedfrom the check presenter 101 by the check-cashing entity 110 may becompared by the biometric input evaluator 920 to data in a repository offingerprint information to determine whether the check presenter 101appears to the person to whom the check is issued.

In FIG. 9C, the activities, functions, and components of thecheck-cashing entity 110 and the check presenter 101 are thussubstantially the same as has been described with reference to FIG. 9B.Similarly, the activities, functions, and components of the checkauthorization system 100 are substantially the same as has beendescribed with reference to FIG. 9B. In FIG. 9C, however, the biometricinput evaluator 920 is configured to access data from a biometric datarepository 930 for use in a comparison with the biometric input obtainedfrom the check presenter 101. In the embodiment depicted in FIG. 9C, thebiometric data repository 930 is a component of the check authorizationsystem 100, and thus communications between the biometric inputevaluator 920 and the biometric data repository 930 take placeinternally to the check authorization system 100. In other embodiments,the biometric data repository 930 resides external to the checkauthorization system 100, and thus communications between the biometricinput evaluator 920 and the biometric data repository 930 take place viaan external communications system. In the embodiment depicted in FIG. 9Cas well as in embodiments in which the biometric data repository resideexternally to the check authorization system 100, the validationroutines 135 and the risk scoring and decisioning component 175 functionin substantially that same way as was described with reference to FIGS.9A and 9B.

FIG. 9D depicts an embodiment in which the check-cashing entity 110obtains biometric input from the check presenter 101 at the time ofpresentment and sends information about the obtained biometric input toa third party biometric evaluation service 940 for evaluation, whileother information obtained in connection with the transaction istransmitted directly to the check authorization system 100. In theembodiment depicted in FIG. 9D, the third party biometric evaluationservice 940 comprises the biometric input evaluator 920 and thebiometric data repository 930. As shown in FIG. 9D, the third partybiometric evaluation service 940 is configured to communicate theresults of its evaluation to the data input component 125 of the checkauthorization system 100. In other embodiments, the third partybiometric evaluation service 940 is configured to communicate theresults of its evaluation back to the check-cashing entity 110, whichthen transmits the results to the data input component 125 of the checkauthorization system 100.

In FIG. 9D, the activities, functions, and components of the checkauthorization system 100 are substantially the same as has beendescribed with reference to FIGS. 9A, 9B, and 9C above.

In the embodiments shown in FIGS. 9A, 9B, 9C, and 9D, the biometric riskscore may be used as one factor in an assessment of the risk associatedwith approving the proposed check-cashing transaction.

The structure and configuration of components and communications linksdepicted in FIGS. 9A, 9B, 9C, and 9D are one of a plurality of possiblestructures and configurations suitable to the purposes of the checkauthorization system 100 described herein. Furthermore, otherembodiments of the systems and methods described herein are envisionedwhich may comprise some, all, or none of the features described withreference to FIGS. 9A, 9B, 9C, and 9D. Thus, FIGS. 9A, 9B, 9C, and 9Dare intended to aid in describing and clarifying the features and not tolimit the description.

FIG. 10 is a flowchart that depicts one embodiment of a process 1000 touse biometric information as a factor in generating a risk score forsecond-party check acceptance. As depicted in FIG. 10, the process 1000begins at a start state and continues to state 1010, where the datainput component 125 receives input, comprising biometric-related inputand other input associated with a proposed check-cashing transactionfrom the check-cashing entity 110. In state 1020, the data inputcomponent 125 identifies the biometric-related input, and, in state1030, determines if the biometric input has already been evaluatedregarding the level of confidence it generates that the check presenter101 is the same person to whom the check was issued.

If the data input component 125 determines in state 1030 that thebiometric input has not yet been evaluated, the data input component 125transmits the biometric input to the biometric input evaluator 920 forevaluation in state 1040. In various embodiments, the biometric inputevaluator 920 may evaluate the biometric input by at least one of:comparing the biometric input with information from an internalrepository of biometric data, comparing the biometric input withinformation from an external repository of biometric data, comparing thebiometric input with additional information received from the checkpresenter, and generating a measure of the level of confidence that thecheck presenter 101 is the correct payee of the check according toanther method.

When the biometric input has been evaluated, the process 1000 continuesfrom state 1040 on to state 1050.

Returning now to state 1030, if the data input component 125 determinesin state 1030 that the biometric input has been evaluated, the process1000 continues on to state 1050, where a biometric risk score isassigned to reflect the evaluated Biometric Confidence level.

As was described with respect to the positive pay risk score referencedin FIG. 4, the biometric risk score may be assigned to the biometricvariable value based on a variety of criteria, business priorities,statistical models, historical observations, and the like. In someembodiments, biometric risk scores are assigned to raw biometricvariable values 420 based on an automated learning or decision-makingalgorithm that identifies risk patterns associated with various variablevalues 420. In some embodiments, biometric risk scores are assigned tobiometric variable values 420 based on a human evaluation of the levelof risk associated with various variable values 420. In someembodiments, biometric risk scores are assigned to biometric variablevalues 420 based on a combination of one or more automated algorithmsand human evaluation. In some embodiments, biometric risk scores areassigned to biometric variable values 420 arbitrarily. In someembodiments, methods used to assign biometric risk scores to biometricvariable values 420 may vary, based at least in part on trends specificto a given industry or type of check-cashing entity 110. In someembodiments, methods used to assign biometric risk scores to biometricvariable values 420 may vary, based at least in part on preferencesexpressed by the check-cashing entity 110.

From state 1050, the process 1000 continues to state 1060, where theassigned biometric risk score may be used in conjunction with riskscores that reflect other aspects of the proposed check-cashingtransaction to calculate a transaction risk score. For example, in oneembodiment, the biometric risk score is used in conjunction with aninsignia-related risk score to provide a transaction risk score withenhanced risk assessment for the check presenter 101 as well as for thepresented check. In another embodiment, a transaction risk score isdetermined based at least in part on a biometric risk score and on apositive pay risk score. In other embodiments, a variety of combinationsof risk scores may be used to determine a transaction risk score, assuits the preferences of the check-cashing entity, the checkauthorization system and other interested parties.

Thus, it may be that, in some embodiments, even with a biometric riskscore indicative of a lower level of confidence in an accurateidentification of the check presenter, if other factors influencing thetransaction risk are sufficiently positive, the transaction risk scoredetermined may be indicative of a recommendation to accept thetransaction.

From state 1060, the process 1000 continues to an end state, where theprocess 1000 is complete. In various embodiments, the transaction riskscore is used to generate an approve/decline recommendation fortransmission to the check-cashing entity 110.

In various embodiments, recommendations based at least in part ontransaction risk scores may be influenced by preferences, businessdecisions, and agreements set by the check-cashing entity 110, such thatthe same transaction risk score could lead to a recommendation toapprove a check-cashing transaction for one check-cashing entity 110 andcould lead to a recommendation to decline a check-cashing transactionfor another check-cashing entity 110.

The flowchart of FIG. 10 describes one embodiment of the process 1000 touse biometric information to generate a risk score for second-partycheck acceptance as comprising various states in which various functionsare carried out. As will be familiar to one of ordinary skill in theart, in other embodiments, the process 1000 may be executed using adifferent order, configuration, or set of states, and the states of theprocess 1000 may perform the functions differently from the embodimentof FIG. 10, without departing from the spirit of process 1000.

Risk Scoring Using Location-Related Information

FIGS. 11A and 11B are block diagrams that depict two embodiments of asystem that uses location-related information to generate a risk scorefor second-party check acceptance. Location-related information may beused to enhance confidence in the cashability of a check presented to acheck-cashing entity for cashing. For example, in some embodiments,checks issued by employers that are local to the check-cashing entity110 may be deemed to pose less risk for cashing than do checks issued byemployers located at a greater distance from the check-cashing entity110. In such embodiments, information about the location of the checkissuer may be accessed by the check authorization system 100 and may beused to determine the proximity of the check issuer to the check-cashingentity 110 and to calculate a risk score for the proposed transaction.

For example, information may exist that categorizes the locations ofbusinesses according to regions, such as Metropolitan Statistical Areas(MSA's) that are used and updated in government census surveys. Asanother example, information may be compiled and maintained by the checkauthorization system 100 or by a third party regarding large employers,government entities, or other check issuers that categorizes thelocations of the check issuers by city, county, state, zip code, timezone, or other categories or regions, or that uses a system such as aglobal positioning system (GPS) or other coordinate system to describethe location of the check issuers.

Other types of location-related and/or proximity-based information thatare found to be useful in enhancing risk assessment for a proposedcheck-cashing transaction may also be used, where permissible by law.For example, in an embodiment configured to authorize the cashing ofgovernment checks, information about the jurisdictions of variouscheck-issuing governmental entities may be useful to the item validationroutines 140 of a check authorization system 100.

In FIGS. 11A and 11B, the check presenter 101 presents a check to acheck-cashing entity 110. The check-cashing entity 110 obtains varioustypes of information associated with the proposed check-cashingtransaction from the check presenter 101, comprising, among other typesof information, information about the issuer of the check beingpresented for cashing. As has been described above, the check issuer maybe an employer or other business entity, government entity, financialentity, other entity, individual, or the like. The information about thecheck issuer may be prompted for explicitly at the check-cashing entity110 or may be extracted from other information obtained in associationwith the check-cashing transaction. For example, the check issuer may beidentified by way of a routing number and account number read from theface of the presented check. The information about the check issuer maycomprise information about the location of the check issuing business ormay allow for stored information about the location of the check issuingbusiness to be accessed. For example, in some embodiments, usinginformation about the checking account on which the presented check isdrawn allows the check authorization system 100 to accesslocation-related information 1100, 1170 for the check issuer.

In various embodiments, information may be obtained by the check-cashingentity 110 using one or more input devices or systems comprising, butnot limited to: a keypad, a voice recognition system, a touchscreen, anoptical character recognition (OCR) reader, a scanner, a smartcardreader, and a stylus.

In some embodiments, if the check authorization system 100 is notinitially able to successfully use the information about the checkissuer received from the check-cashing entity 110, the checkauthorization system 100 may transmit an indication to that effect tothe check-cashing entity 110, and a prompt may be displayed to anoperator at the check-cashing entity 110 to input additional informationabout the check-issuer. For example, if the check authorization system100 is not able to access location-related information about a checkissuer using information from the MICR-line of the presented check, theoperator at the check-cashing entity may be prompted to type in addressinformation about the check issuer. In other embodiments, the operatormay be prompted to enter information about the check issuer name, checkissuer bank account identifier, and location information. In someembodiments, the additional information entered may be stored in therepository of location-related information 1170 for use in associationwith subsequent transactions.

As was described in greater detail with reference to FIG. 1, thecheck-cashing entity 110 transmits information related to the proposedcheck-cashing transaction 110 to the data input component 125 of thecheck authorization system 100 via a communications interface. The datainput component 125 transmits at least some of the information to thevalidation routines 135 for processing by the item validation 140, theperson validation 150, and the location validation 160 routines.

As depicted in FIGS. 11A and 11B, the location validation routines 160access location-related information 1100, 1170 in order to assesslocation-related factors associated with the proposed check-cashingtransaction, such as the proximity of the check-issuing business to thecheck-cashing entity's location 110.

Location-related information 1100, 1170 that is used by the itemvalidation routines 140 of a check authorization system 100 may bestored externally or internally to the check authorization system 100.FIG. 11A depicts an embodiment in which the item validation routines 140access enterprise listings by area 1150 from a source oflocation-related information 1100 that is located externally to thecheck authorization system 100. For example, information available fromthe U.S. Census Bureau or other government entity, from a businessbureau, or from a third-party source of location information may beaccessed externally by the check authorization system 100.

FIG. 11B depicts an embodiment in which location-related information1170 is compiled and maintained by the check authorization system 100and can be accessed by the item validation routines 140 internally. Oneembodiment of an internal repository of location-related information1170 is described in greater detail with reference to FIG. 11C below.

In some embodiments, the location validation routines 160 may accessinformation about the check-cashing entity's location 110 as well asinformation about the check issuer's location in order to make acomparison between the two. In some embodiments, information about thecheck-cashing entity's location 110 may be stored at the checkauthorization system 100. In some embodiments, information about thecheck-cashing entity's location 110 may be transmitted to the checkauthorization system 100 at the time of check presentment or may beobtained by the check authorization system 100 according to anothermethod.

In some embodiments, the comparison between the check-cashing entitylocation 110 and the check issuer location may yield a result that isexpressed in terms of distance, such as miles distance between thecheck-cashing entity 110 and the check issuer. In some embodiments, thecomparison may yield a result that is expressed in terms of a number ofMSA's, counties, zip code areas, telephone area code areas, or the likethat are crossed to navigate from the check-cashing entity 110 to thecheck issuer. In some embodiments, the comparison may yield a resultthat is expressed in terms of a category, such as YES/NO categories foran embodiment that determines whether the check-cashing entity 110 andthe check issuer are located in the same MSA, or as, for example, one ofa set of proximity-based categories, such as LOCAL, MID_RANGE, andDISTANT for expressing distances of varying amounts.

As depicted in FIGS. 11A and 11B, in some embodiments, a comparison ofthe check issuer's location with the check-cashing entity's 110 locationmay be performed by the risk scoring and decisioning component 175 ofthe check authorization system 100. For example, information about thecheck-cashing entity's 110 location may be passed to the risk scoringand decisioning component 175 by the data input component 125, andinformation about the check issuer's location may be passed to the riskscoring and decisioning component 175 by the validation routines 135.

In various embodiments, the location validation routines 160 or the riskscoring and decisioning component 175 may assign a location-related riskscore based at least in part on the location-related informationassociated with the proposed transaction.

Based on the needs, preferences, and characteristics of a check-cashingentity 110, location-related proximity information may be evaluated andused according to different guidelines, oftentimes referred to as“rules.” Thus, definitions of what constitutes a “local” business, a“non-local” business, a long distance, a short distance, or any distancein between may be defined as suits the risk assessment preferences ofthe check-cashing entity 110, through customized rules. For example,risk assessment rules for checks presented at a convenience store in asmall rural town may assign a score indicative of higher risk when thechecks are issued by employers located at a long distance from the townthan would risk assessment for checks presented at a resort thatfrequently hosts visitors from the same long distance.

As was described in greater detail with reference to FIG. 4 above, thelocation-related risk score 430 expresses a level of perceived riskassociated with the location-related information, expressed as one ormore location-related variable values 420. In various embodiments, alocation-related risk score 430 may be assigned to location-relatedvariable values 420 based on a variety of criteria, business priorities,statistical models, historical observations, and the like. In someembodiments, location-related risk scores are assigned tolocation-related variable values 420 based on an automated learning ordecision-making algorithm that identifies risk patterns associated withvarious variable values 420. In some embodiments, location-related riskscores 430 are assigned to location-related variable values 420 based ona human evaluation of the level of risk associated with various variablevalues 420. In some embodiments, location-related risk scores areassigned to location-related variable values 420 based on a combinationof one or more automated algorithms and human evaluation. In someembodiments, location-related risk scores are assigned tolocation-related variable values 420 arbitrarily. In some embodiments,methods used to assign location-related risk scores to location-relatedvariable values 420 may vary, based at least in part on trends specificto a given industry or type of check-cashing entity 110. In someembodiments, methods used to assign location-related risk scores tolocation-related variable values 420 may vary, based at least in part onpreferences expressed by the check-cashing entity 110.

The location-related risk score 430 may be used alone or may be combinedwith other risk scores to calculate a more comprehensive risk score 440for the proposed check-cashing transaction. For example, in oneembodiment, a more comprehensive transaction risk score 440 may be basedon the location-related risk score as well as on biometric informationobtained from an individual presenting a check for cashing.

The structure and configuration of components and communications linksdepicted in FIGS. 11A and 11B are one of a plurality of possiblestructures and configurations suitable to the purposes of the checkauthorization system 100 described herein. Furthermore, otherembodiments of the systems and methods described herein are envisionedwhich may comprise some, all, or none of the features described withreference to FIGS. 11A and 11B. Thus, FIGS. 11A and 11B are intended toaid in describing and clarifying the features and not to limit thedescription.

FIG. 11C depicts one embodiment of a repository of location-relatedinformation 1170 about check issuers. In various embodiments, therepository 1170 may be compiled and maintained by the checkauthorization system 100 or by an external third party service. Invarious embodiments, the repository 1170 is stored on acomputer-accessible storage medium.

For example, the repository 1170 may be a database of location-relatedinformation for employers who operate within a given proximity to one ormore check-cashing entities 110. Compiling the database may compriseidentifying employers in a desired geographical location, such as withintwenty miles of a given check-cashing entity 110 or within the samecounty as the check-cashing entity 110, and creating records for theemployers, wherein information about an employer, such as an employername, and an associated employer location are stored within a record. Insome embodiments, identifying employers or other check issuers within adesired geographical comprises identifying employers in a desiredgeographical location further comprises identifying employers within adesired region defined by at least one of the set consisting of: zipcode, city, county, state, telephone area code, and MetropolitanStatistical Area (MSA). In some embodiments, check issuers for whomrecords are compiled in the repository 1170 may be from any geographicallocation. In some embodiments, the records may be compiled for employerswithin the desired geographical location who are above a minimumthreshold in size, as measured by number of employees, net worth, orsome by some other measure.

In some embodiments, compiling the database may further compriseobtaining from the employers identifiers for checking accounts that theemployers use for issuing payroll checks to their employees and storinginformation about the checking account identifiers in the associatedrecords of the repository. An identifier for a checking account on whicha check is being drawn may frequently be obtained from the check when itis being presented for cashing. Thus, obtaining the check accountidentifier may allow for accessing the employer location informationstored in the repository 1170.

In the embodiment shown in FIG. 11C, location information for the checkissuer of a check presented for cashing may be accessed usingidentification information about a bank checking account on which thecheck is drawn. The identification information about the bank checkingaccount may be available from a variety of sources, for example: using amagnetic ink reader to read a MICR-line on the face of the check, usingoptical character recognition (OCR) technology to read an imprinted bankand account number from the face of the check, having an operator of thedata input device 115 at the check-cashing entity 110 read the check andmanually or verbally and input bank and account number from the check,or by another currently-available or future-available method, as will befamiliar to one of ordinary skill in the art.

The embodiment of the repository of location-related information 1170,as depicted in FIG. 11C, comprises four or more fields 1171-1174 usefulfor accessing location-related information for risk scoring. A banknumber field 1171 and an account number field 1172 allow for accurateidentification of a bank account associated with the presented check.When the repository 1170 comprises records referring to accounts frommultiple banks, as is frequently the case, the bank number field 1171and the account number field 1172, used in conjunction, may beconsidered to be an identifier for the account referred to in a record.In embodiments where the repository 1170 comprises records that refer toaccounts in one bank, the bank number field 1171 may not be necessaryfor accurate identification of an account and its associated checkissuer. A payor name field 1173 provides information about a nameassociated with the check issuer. Payor name information 1173 may beuseful, for example, for verifying correct identification of the checkissuer, or, as another example, may be used as an input in otherembodiments for accessing payor location information.

A payor location field 1174 stores information about the location of acheck issuer useful for determining a location-based risk score for thecheck-cashing transaction. In various embodiments, the payor locationfield 1174 may describe the payor location using at least one of: astreet address, city identifier, county identifier, state identifier,zip code, telephone area code, metropolitan statistical area (MSA)identifier, GPS or other geographical coordinate descriptor, or othertype of location identifier. Information from the payor location field1174 may, in some embodiments, be used on its own to determine alocation-based risk score, or may be used in combination with otherinformation, such as location information for the check-cashing entity110, to determine a location-based risk score for the check-cashingtransaction. For example, the check authorization system 100 maycalculate a distance between the payor location and the check-cashingentity 110 location. As another example, the check authorization system100 may determine whether the payor location and the check-cashingentity 110 location are situated in the same zip code area, or the like,or whether the check-cashing entity 110 location payor location aresituated in nearby zip code areas, or the like. Thus information aboutthe proximity of the payor location and the check-cashing entity 110location may be used for risk scoring purposes.

In other embodiments, the repository of location-related information1170 may additionally or alternatively comprise other fields, such asone or more fields indicating whether the check issuer operates officesor other facilities located across multiple areas, such as a nationalcorporation with branches in a plurality of states. In some embodiments,other information about the check issuers, such as number of years inbusiness or employer size, based, for example, on number of employees ornet worth, may be stored in the repository 1170 to provide additionalinformation deemed to be useful to an assessment of the risk involved inaccepting a check issued by the check issuer.

In some embodiments, one or more fields in the repository oflocation-related information 1170 may store pre-determined orpre-calculated proximity information for a given check issuer and one ormore locations, such as for one or more check-cashing entity locations110. For example, average distance information for a given check issuerand check-cashing entities 110 in various regions may be pre-calculatedand stored in the repository 1170. Using such pre-determined proximityinformation, the check authorization system 100 may, in someembodiments, determine a location-related risk score for a checktransaction without needing to use valuable computer processor time todetermine or to calculate proximity information for the individual checktransaction. In other embodiments, other types of pre-determined orpre-calculated location-related information may be stored in order toexpedite location-based risk scoring by the check authorization system100. In other embodiments, other types of geographic-related data forthe check issuer and/or for the check-cashing entity 110 may be storedin the repository 1170.

Other fields, other embodiments of the repository of location-relatedinformation 1170, and other types of location-based information that mayenhance a risk assessment of a financial transaction usinglocation-based information are envisioned as embodiments of the systemsand methods described herein without departing from the spirit of theinvention.

In some embodiments of the systems and methods described herein, if acheck presenter 101 presents a check with a check account identifierthat does not appear in the repository of location-related information1170, the check authorization system 100 may update the repository byrequesting from the check-cashing entity 100 that is processing thetransaction information about at least one of: an employer name, anemployer bank account identification, and employer location informationassociated with the presented check, and adding the information receivedfrom the check-cashing entity 110 to the repository 1170. In someembodiments, the check authorization system 100 may transmit a messageto the check-cashing entity 110 that causes a prompt to appear to anoperator of a point-of-sale device at the check-cashing entity 110,requesting that the operator input the desired information.

FIG. 12 is a flowchart that depicts one embodiment of a process 1200 touse location-related information to generate a risk score forsecond-party check acceptance. The process 1200, as depicted in FIG. 12,begins at a start state and moves to state 1210 where the data inputcomponent 125 of the check authorization system 100 receives input abouta proposed check-cashing transaction from a check-cashing entity 110. Asdescribed with reference to FIG. 1, the input may comprise informationabout the check presenter, information about the check item, and otherinformation useful for assessing the risk associated with accepting thecheck for cashing.

Moving on to state 1220, the input is transmitted to the validationroutines 135, where a subset of the input that is useful for accessinglocation-related information is identified. In various embodiments,different types of input may be used to access location-relatedinformation. For example, in some embodiments, MICR-line informationobtained from the face of the check provides identification for a bankand account number associated with the check. In embodiments where thecheck authorization system 100 has access to a suitably configuredrepository of information, location-related information for the checkissuer may be accessed using the MICR-line information.

In other embodiments, the input useful for locating the desiredlocation-related information may be at least one of: a business name forthe check issuer and/or an address or other identifying information forthe issuer of the check. In other embodiments, other data received bythe data input component 125 may be useful in locating location-relatedinformation.

Moving on to state 1230, the location-related input is used in anattempt to locate associated location-related information about thecheck issuer from a suitable repository of location-related data 1100,1170.

Moving on to state 1240, the process 1200 determines if the attempt tolocate associated location-related information about the check issuerwas successful. If the attempt was successful, the process 1200 moves onto state 1245 and a location-related variable value 420, as is describedwith reference to FIG. 4 is determined, based at least in part on theaccessed location-related information. For example, a distance in milesfrom the check-cashing entity 110 to the check issuer location may becalculated as used as the location-related variable value 420. As isexemplified with reference to the example score calculations of FIG. 4,the issuer of the presented check may, in some embodiments, becharacterized as being a “LOCAL” employer, a “NON-LOCAL” employer, or an“NOT AVAIL” employer for which location data is unavailable. In otherembodiments, other systems for categorizing the transaction based on thelocation-related information may be used, as will be familiar to one ofordinary skill in the art.

Returning now to state 1240, if, in state 1240, the process 1200determines that location-related information was not found in therepository, the process moves to state 1242, where a message is sent tothe check-cashing entity 110, requesting additional input. In someembodiments, a message is displayed to an operator at the check-cashingentity 110, prompting the operator to request additionallocation-related information from the check-presenter 101 or tootherwise obtain additional location-related information.

In some embodiments, if no location-related information associated withthe bank account identified in the check's MICR-line was found in therepository, and if additional input obtained from the check presenter101 and the check-cashing entity 110 is able to provide location-relatedinformation for the check issuer, the check authorization system 100adds the newly-obtained location-related information for the checkissuer to the repository. For example, in one embodiment, the checkauthorization system 100 may create a record in the repository withMICR-line information from the check and with information about thecheck issuer's name and location obtained from the check presenter 101and/or from information imprinted on the check.

Once location-related information for the check issuer has beenobtained, the process 1200 moves on to state 1245, where alocation-related variable value 420, is determined, based at least inpart on the accessed location-related information, as described ingreater detail above.

From state 1245, the process 1200 moves on to state 1250 where the itemvalidation routines 140 assign a location-related risk score 430 to thetransaction based on the location-relation variable value.

As was described in greater detail with reference to FIG. 4 above, thelocation-related risk score expresses a level of perceived riskassociated with the location-related variable value 420. In variousembodiments, a location-related risk score may be assigned tolocation-related variable values 420 based on a variety of criteria,business priorities, statistical models, historical observations, andthe like. In some embodiments, location-related risk scores are assignedto location-related variable values 420 based on an automated learningor decision-making algorithm that identifies risk patterns associatedwith various variable values 420. In some embodiments, location-relatedrisk scores are assigned to location-related variable values 420 basedon a human evaluation of the level of risk associated with variousvariable values 420. In some embodiments, location-related risk scoresare assigned to location-related variable values 420 based on acombination of one or more automated algorithms and human evaluation. Insome embodiments, location-related risk scores are assigned tolocation-related variable values 420 arbitrarily. In some embodiments,methods used to assign location-related risk scores to location-relatedvariable values 420 may vary, based at least in part on trends specificto a given industry or type of check-cashing entity 110. In someembodiments, methods used to assign location-related risk scores tolocation-related variable values 420 may vary, based at least in part onpreferences expressed by the check-cashing entity 110.

Moving on to state 1260, the item validation routines 140 transmit thelocation-related score 430 to the risk scoring and decisioning component175 of the check authorization system 100. As was described in greaterdetail with reference to FIG. 4, the location-related risk scorereflects a perceived level of risk associated with approving atransaction with the assigned location-related category orcharacteristic.

Moving on to state 1270, the risk scoring and decisioning component 175integrates the assigned location-related score with other scoringvariables that reflect risk associated with other aspects of theproposed check-cashing transaction, such as, for example, the checkamount, biometric input of the check presenter 101, and/or positive payinformation associated with the check, as was exemplified with referenceto the score calculations of FIG. 4. Based at least in part on thelocation-related risk score, the risk scoring and decisioning component175 calculates a risk score 440 for the proposed transaction, and theprocess 1200 to use location-related information as a factor in a riskscoring calculation for a check-cashing transaction is complete.

In one embodiment, the process 1200 is used as part of a larger riskassessment process for check-cashing transactions, in which the riskscoring and decisioning component 175 transmits a recommendation toapprove or to decline the proposed check-cashing transaction to thecheck-cashing entity 110, based at least in part on the transaction riskscore 440 calculated by the process 1200.

In various embodiments, recommendations based at least in part ontransaction risk scores may be influenced by preferences, businessdecisions, and agreements set by the check-cashing entity 110, such thatthe same transaction risk score could lead to a recommendation toapprove a check-cashing transaction for one check-cashing entity 110 andcould lead to a recommendation to decline a check-cashing transactionfor another check-cashing entity 110.

The flowchart of FIG. 12 describes one embodiment of the process 1200for using location-related information to generate a risk score forsecond-party check acceptance as comprising various states in whichvarious functions are carried out. As will be familiar to one ofordinary skill in the art, in other embodiments, the process 1200 may beexecuted using a different order, configuration, or set of states, andthe states of the process 1200 may perform the functions differentlyfrom the embodiment of FIG. 12, without departing from the spirit ofprocess 1200.

Risk Scoring Using Information about Authentication Marks

FIGS. 13A, 13B, and 13C are block diagrams that depict three embodimentsof a system that uses authentication marks or other insignia-relatedinformation to generate a risk score for second-party check acceptance.Authentication mark are marks or devices incorporated into a check orother negotiable instrument that are difficult and/or costly forcounterfeiters to reproduce and that thus help to distinguish alegitimate check or negotiable instrument from a counterfeit. Examplesof authentication marks comprise, but are not limited to, watermarks,security validation numbers, bar codes, insignia, background patterns,color schemes, colorshifting ink, holographic strips, ultraviolet lightsensitive fibers, encryption, and other marks or devices which may serveto enhance confidence in the authenticity of the check, in addition toor as an alternative to features that serve to identify a check and itsassociated bank account. Insignia-related information may be used toenhance confidence in the cashability of a check presented to acheck-cashing entity for cashing. Other types of insignia-related and/orauthentication-mark-based information that are found to be useful inenhancing risk assessment for a proposed check-cashing transaction mayalso be used.

In FIGS. 13A, 13B, and 13C, the check presenter 101 presents a check toa check-cashing entity 110. The check-cashing entity 110 obtains varioustypes of information associated with the proposed check-cashingtransaction from the check presenter 101, comprising, among other typesof information, information about authenticating marks on the checkbeing presented for cashing, which may be obtained using aninsignia-related input device 1310 other type of graphic input system.The information about the authenticating mark, or insignia, may, invarious embodiments, comprise one or more electronically captured imagesof the insignia. In some embodiments, information about theauthenticating mark may comprise a front image and a back image of theauthenticating mark. In some embodiments, information about theauthenticating mark may comprise a front and back image of the presentedcheck or other negotiable instrument. In some embodiments, informationabout the authenticating marks is input manually or verbally by anoperator of an input device 115 at the check-cashing entity 110.

In various embodiments, insignia-related input from the presented checkis evaluated by comparing it to an expected image, configuration, orcharacteristic for the authentication mark. In some embodiments,insignia-related input from the presented check is evaluated based oninformation other than a stored image, such as, for example, on rulesthat describe a correct or acceptable version of the authenticatingmark. Stored insignia-related information, such as a database ofexpected images of authenticating marks or another repository of rulesor other information associated with authenticating marks, may be usedfor comparing with insignia-related input obtained in conjunction with aproposed check-cashing transaction. As will be described with referenceto FIGS. 13A, 13B, and 13C, the insignia-related information may bestored externally and/or internally to the check authorization system100.

In various embodiments, insignia-related evaluation generates anexpression of a perceived degree of similarity between aninsignia-related input regarding a check's authenticating mark or marksand an expected image or configuration of the authenticating mark ormarks. The insignia-related input may, in various embodiments, be anumeric expression, a category-based expression, or another expressionof the perceived similarity between the insignia-related input and theexpected configuration for the authenticating mark.

FIGS. 13A, 13B, and 13C differ from one another in that, in FIG. 13A,evaluation of the insignia-related input takes places at thecheck-cashing entity 110 before transmission of transaction-related datato the check authorization system 100, while in FIG. 13B, evaluation ofthe insignia-related input takes places at the check authorizationsystem 100, and in FIG. 13C evaluation of the insignia-related inputtakes places at a third party service provider 1350.

In the embodiment shown in FIG. 13A, evaluation of the insignia-relatedinput takes places at the check-cashing entity 110. In the embodimentshown, the check-cashing entity 110 comprises an insignia-related inputgenerator 1300 that comprises both the insignia-related input device1310 and an input evaluator 1320 for evaluating the insignia-relatedinput. In some embodiments, the insignia-related input device 1310further comprises a repository of insignia-related information forcomparison with the obtained input form the presented check. In otherembodiments, the check-cashing entity 110 may comprise other hardwareand/or software resources for evaluating authenticating marks on checkspresented for cashing. The evaluated insignia-related input is thentransmitted to the data input component 125 of the check authorizationsystem 100, as is other input associated with a proposed check-cashingtransaction.

In the embodiment shown in FIG. 13B, evaluation of the insignia-relatedinput takes places at the check authorization system 100. Thecheck-cashing entity 110 sends insignia-related input obtained by theinsignia-related input device 1310 along with other data associated withthe proposed check transaction to the data input component 125 of thecheck authorization system 100. The data input component 125 sends theinsignia-related input received from the check-cashing entity 110 to aninternal insignia-related input evaluator 1330 for evaluation. In theembodiment shown in FIG. 13B, the insignia-related input evaluator 1330comprises an insignia-related data repository 1340 for comparison withthe insignia-related data obtained from the presented check. Theevaluated insignia-related input is then transmitted to the itemvalidation routines 140 for further processing.

In the embodiment shown in FIG. 13C, evaluation of the insignia-relatedinput takes places at a third-party insignia-related input evaluationservice 1350. The check-cashing entity 110 sends insignia-related inputobtained by the insignia-related input device 1310 to the third-partyinsignia-related input evaluation service 1350 for evaluation. As shownin FIG. 13C, the third-party insignia-related input evaluation service1350 comprises an insignia-related input evaluator 1360 which may use aninsignia-related data repository 1370 for comparison with the obtainedinput from the presented check. In the embodiment depicted in FIG. 13C,the third-party insignia-related input evaluation service 1350 transmitsthe evaluated insignia-related input to the data input component 125 ofthe check authorization system 100. In other embodiments, thethird-party insignia-related input evaluation service 1350 transmits theevaluated insignia-related input back to the check-cashing entity 110for transmission, together with other information related to theproposed check transaction, to the data input component 125 of the checkauthorization system 100.

In some embodiments, the item validation routines 140 calculate and/orassign an insignia-related risk score to the transaction based at leastin part on the insignia-related evaluation to expresses a level ofperceived risk associated with the insignia-related evaluation. Invarious embodiments, an insignia-related risk score may be assigned toinsignia-related evaluations based on a variety of criteria, businesspriorities, statistical models, historical observations, and the like.In some embodiments, insignia-related risk scores are assigned toinsignia-related evaluations based on an automated learning ordecision-making algorithm that identifies risk patterns associated withvarious evaluations. In some embodiments, insignia-related risk scoresare assigned to insignia-related evaluations based on a human evaluationof the level of risk associated with various evaluations. In someembodiments, insignia-related risk scores are assigned toinsignia-related evaluations based on a combination of one or moreautomated algorithms and human evaluation. In some embodiments,insignia-related risk scores are assigned to insignia-relatedevaluations arbitrarily. In some embodiments, methods used to assigninsignia-related risk scores to insignia-related evaluations may vary,based at least in part on trends specific to a given industry or type ofcheck-cashing entity 116. In some embodiments, methods used to assigninsignia-related risk scores to insignia-related evaluations may vary,based at least in part on preferences expressed by the check-cashingentity 110.

Based on the needs, preferences, and characteristics of a check-cashingentity 110, insignia-related information may be evaluated and usedaccording to different guidelines, oftentimes referred to as “rules.”Thus, definitions of what constitutes an acceptable watermark or barcode scan, or other authenticating insignia data capture may be definedas suits the risk assessment needs of the check-cashing entity 110,through customized rules. For example, a bar code printed on the face ofa check by a local employer may be known to frequently become smudged,distorted, or otherwise deteriorated when kept in an employee's pocket,often folded, and the like, whereas a watermark used on the checks ofanother employer may not. A local check-cashing entity 110 may recognizethat the bar coded checks, while legitimate, more frequently producedegraded insignia-related input. The check-cashing entity 110 may bewilling to accept the bar coded checks, even with a lower degree ofsimilarity between the input barcodes and the expected images, whilestill demanding a higher degree of similarity between the watermarks andtheir expected configurations for the watermarked checks.

In some embodiments, the item validation routines 140 do not assign orcalculated the insignia-related risk score, and instead the itemvalidation routines 140 transmit the insignia-related evaluation to therisk scoring and decisioning component 175 for generation of aninsignia-related risk score.

The insignia-related risk score may be used alone or may be combinedwith other risk scores to calculate a more comprehensive transactionrisk score for the proposed check-cashing transaction. For example, aninsignia-related risk score may be combined with a biometric risk scorebased at least in part on data that is received from an auxiliarybiometric input system. Furthermore, the check authorization system 100may transmit an accept/decline recommendation to the check-cashingentity 110 based at least in part on the transaction risk score. Invarious embodiments, recommendations based at least in part ontransaction risk scores may be influenced by preferences, businessdecisions, and agreements set by the check-cashing entity 110, such thatthe same transaction risk score could lead to a recommendation toapprove a check-cashing transaction for one check-cashing entity 110 andcould lead to a recommendation to decline a check-cashing transactionfor another check-cashing entity 110.

The structure and configuration of components and communications linksdepicted in FIGS. 13A, 13B, and 13C are one of a plurality of possiblestructures and configurations suitable to the purposes of the checkauthorization system 100 described herein. Furthermore, otherembodiments of the systems and methods described herein are envisionedwhich may comprise some, all, or none of the features described withreference to FIGS. 13A, 13B, and 13C. Thus, FIGS. 13A, 13B, and 13C areintended to aid in describing and clarifying the features and not tolimit the description.

FIG. 14 is a flowchart that depicts one embodiment of a process 1400 touse insignia-related information to generate a risk score forsecond-party check acceptance. In various embodiments, insignia-relatedinformation about a check that is presented for cashing may comprise oneor more watermarks, bar codes, insignia, background patterns,microprinting, colorshifting ink, holographic strips, securityvalidation numbers, ultraviolet light sensitive fibers, or otherauthenticating marks or devices from the check that may be used toenhance the ability to distinguish checks that are legitimate fromchecks that are not legitimate.

Insignia-related input obtained by the check-cashing entity 110 from thecheck being presented by the check presenter 101 may be compared tostored and/or expected insignia-related information, as will bedescribed in greater detail below. Insignia-related information may thusbe used to enhance confidence in the accurate identification of thecheck item and may enhance confidence that the check item is legitimate.By incorporating insignia-related input in a risk scoring system forcheck cashing, an assessment of the check item's legitimacy may beconsidered along with other factors indicative of a level of securityassociated with accepting a proposed check-cashing transaction. Forexample, in one embodiment an insignia-related risk score may express aconfidence level in the legitimacy of the presented check and abiometric risk score may express a confidence level in the accurateidentification of the check presenter, and a combined use of the tworisk scores may provide an enhanced risk assessment for the transaction.By allowing for a gradated expression of the assessed degree ofconfidence based on the insignia-related input, allowances may be madefor checks whose authenticating marks compare less than perfectly withan expected configuration for the authenticating mark.

The process 1400, as depicted in FIG. 14, begins at a start state andmoves to state 1410 where insignia-related information for a proposedtransaction is obtained from the check item by the check-cashing entity110 using one or more of a wide array of possible input devices 115,such as, but not limited to, scanners, cameras, lights, readers, andother specialized devices. In some embodiments, a point-of-sale deviceat the check-cashing entity 110 displays a prompt to an operator of thepoint-of-sale device to input insignia-related information about anauthenticating mark from the presented check. In some embodiments,insignia-related information is machine-read input electronically. Inother embodiments, the operator of the point-of-sale device inputs theinsignia-related information. In other embodiments, a combination of thetwo methods or another method is used to obtain the insignia-relatedinformation about the authenticating mark.

Moving on to state 1420, the insignia-related input is identified andtransmitted to an insignia-related evaluator. In the embodimentsdepicted in FIGS. 13A and 13C, the insignia-related input is identifiedfor transmission to an insignia-related evaluator by the check-cashingentity 110. In FIG. 13A, the check-cashing entity 110 identifies theinsignia-related input and transmits it to an internal insignia-relatedinput generator 1300 for evaluation. In FIG. 13A, the check-cashingentity 110 identifies the insignia-related input and transmits it to athird-party insignia-related evaluation service 1350 for evaluation. InFIG. 13B, the check-cashing entity 110 transmits data associated withthe proposed check-cashing transaction to the data input component 125of the check authorization system. In FIG. 13B, the data input component125 identifies the insignia-related input and transmits it to aninsignia-related input evaluator 1330 internal to the checkauthorization system 100 for evaluation.

Moving on to state 1430, the insignia-related input is evaluated. Invarious embodiments, the insignia-related input is evaluated as comparedwith known or expected insignia configurations. In some embodiments, theevaluation may yield a numeric assessment of the similarity between theinsignia-related input and one or more known or expected configurations.For example, the insignia-related evaluation may yield a percentage thatdescribes the extent to which the insignia-related input matches theexpected configuration. In other embodiments, the evaluation may yield acategory-based assessment of the similarity between the insignia-relatedinput and one or more known or expected configurations. In still otherembodiments, the evaluation may yield another type of assessment of thesimilarity between the insignia-related input and one or more known orexpected configurations.

In various embodiments, the insignia-related evaluation of state 1430may be carried out by the insignia-related input generator 1300, asdescribed with reference to FIG. 13A, by the insignia-related inputevaluator 1330, as described with reference to FIG. 13B, by athird-party insignia-related evaluation service 1350, as described withreference to FIG. 13C, or in another manner, as will be familiar to oneof ordinary skill in the art.

Moving on to state 1440, the evaluated insignia-related input isassigned an insignia-related risk score that expresses a level ofconfidence that the presented check is legitimate, based on theevaluated authenticating mark from the check. In some embodiments, theinsignia-related risk score is indicative of lower risk when theinsignia-related input is evaluated as being more similar to an expectedconfiguration for the authenticating mark, and indicative of higher riskwhen the insignia-related input is evaluated as being less similar to anexpected configuration for the authenticating mark. In variousembodiments, assignment of an insignia-related risk score may be carriedout by the item validation routines 140 or by the risk scoring anddecisioning component 175 of the check authorization system 100.

As was described with respect to the factor risk scores 430 referencedin FIG. 4, factor risk scores 430, of which the insignia-related riskscore is an example, may be assigned based on a variety of criteria,business priorities, statistical models, historical observations, andthe like. In some embodiments, insignia-related risk scores are assignedto raw insignia-related variable values 420 based on an automatedlearning or decision-making algorithm that identifies risk patternsassociated with various variable values 420. In some embodiments,insignia-related risk scores are assigned to insignia-related variablevalues 420 based on a human evaluation of the level of risk associatedwith various variable values 420. In some embodiments, insignia-relatedrisk scores are assigned to insignia-related variable values 420 basedon a combination of one or more automated algorithms and humanevaluation. In some embodiments, insignia-related risk scores areassigned to insignia-related variable values 420 arbitrarily. In someembodiments, methods used to assign insignia-related risk scores toinsignia-related variable values 420 may vary, based at least in part ontrends specific to a given industry or type of check-cashing entity 110.In some embodiments, methods used to assign insignia-related risk scoresto insignia-related variable values 420 may vary, based at least in parton preferences of the check-cashing entity 110.

In various embodiments, the insignia-related evaluation of state 1430may be carried out by the insignia-related input generator 1300, asdescribed with reference to FIG. 13A, by the insignia-related inputevaluator 1330, as described with reference to FIG. 13B, by athird-party insignia-related evaluation service 1350, as described withreference to FIG. 13C, or in another manner, as will be familiar to oneof ordinary skill in the art.

Moving on to state 1450, the item validation routines 140 transmit theassigned insignia-related risk score along with other risk scoresassigned by the person validation routines and the location validationroutines 160 to the risk scoring and decisioning component 175 of thecheck authorization system 100. As was described in greater detail withreference to FIG. 4, the assigned factor risk scores 430, of which theinsignia-related risk score is, in some embodiments, an example, reflecta perceived level of risk associated with approving a transaction, inthis case with the assigned insignia-related evaluation.

In state 1460, the risk scoring and decisioning component 175 integratesthe assigned insignia-related score with other scoring variables thatreflect risk associated with other aspects of the proposed check-cashingtransaction, such as, for example, the check amount, a biometricinformation obtained from the check presenter 101, location-basedinformation for the check issuer, and/or positive pay informationassociated with the check, as was exemplified with reference to thescore calculations of FIG. 4. Based at least in part on theinsignia-related risk score, the risk scoring and decisioning component175 calculates a risk score 440 for the proposed transaction, and theprocess 1400 to use insignia-related information as a factor in a riskscoring calculation for a check-cashing transaction is complete.

In one embodiment, the process 1400 is used as part of a larger riskassessment process for check-cashing transactions, in which the riskscoring and decisioning component 175 transmits a recommendation toapprove or to decline the proposed check-cashing transaction to thecheck-cashing entity 110, based at least in part on the transaction riskscore 440 calculated by the process 1400.

The flowchart of FIG. 14 describes one embodiment of the process 1400for using insignia-related information to generate a risk score forsecond-party check acceptance as comprising various states in whichvarious functions are carried out. As will be familiar to one ofordinary skill in the art, in other embodiments, the process 1400 may beexecuted using a different order, configuration, or set of states, andthe states of the process 1400 may perform the functions differentlyfrom the embodiment of FIG. 14, without departing from the spirit ofprocess 1400.

Although the foregoing invention has been described in terms of certainpreferred embodiments, other embodiments will be apparent to those ofordinary skill in the art from the disclosure herein. Additionally,other combinations, omissions, substitutions and modifications will beapparent to the skilled artisan in view of the disclosure herein. Whilecertain embodiments of the inventions have been described, theseembodiments have been presented by way of example only, and are notintended to limit the scope of the inventions. Indeed, the novel methodsand systems described herein may be embodied in a variety of other formswithout departing from the spirit thereof. The accompanying claims andtheir equivalents are intended to cover such forms or modifications aswould fall within the scope and spirit of the invention.

1. A method of compiling a computer-accessible repository of employerlocation information for use in assessing the risk of a payrollcheck-cashing transaction, the method comprising: identifying employersin a desired geographical location; obtaining from the employersidentifiers for checking accounts associated with the employers, whereinthe checking accounts are accounts drawn on by the employers for writingpayroll checks; compiling on a computer-accessible storage medium arepository of records, wherein a record comprises information toidentify an employer location and at least one of: an associatedemployer name and the associated employer checking account; in responseto receiving a request to cash a payroll check for which the repositoryof records does not hold associated employer information, requestingfrom a check-cashing entity that is processing the request informationabout at least one of: an employer name, an employer bank accountidentification, and employer location information; and adding theemployer information received from the check-cashing entity to therepository.
 2. The method of claim 1, wherein identifying employers in adesired geographical location further comprises identifying employerswithin a desired proximity of the check-cashing entity.
 3. The method ofclaim 1, wherein identifying employers in a desired geographicallocation further comprises identifying employers within a desired regiondefined by at least one of the set consisting of: zip code, city,county, state, telephone area code, and Metropolitan Statistical Area(MSA).
 4. The method of claim 1, wherein requesting information from acheck-cashing entity comprises displaying a prompt to an operator of apoint-of-sale device at the check-cashing entity to input the requestedinformation.
 5. The method of claim 1, wherein identifying employers ina desired geographical location further comprises identifying employersof a desired size.
 6. The method of claim 1, wherein compiling therecords further comprises compiling records that comprise an indicationof a size associated with the employer.
 7. The method of claim 1,wherein compiling the records further comprises compiling records thatcomprise an indication of a number of employees associated with theemployer.
 8. The method of claim 1, further comprising: accessinginformation about an employer location associated with a payroll checkpresented for cashing; using the information to determine a proximityfor the employer location and a location associated with thecheck-cashing transaction; and assessing risk associated with thecheck-cashing transaction based at least in part on the proximity.
 9. Amethod of compiling a computer-accessible repository of check issuerlocation information for use in check transaction risk assessment, themethod comprising: identifying check issuers in a desired geographicallocation; obtaining from the check issuers identifiers for checkingaccounts associated with the check issuers; and compiling on acomputer-accessible storage medium a repository of records, wherein arecord comprises information to identify a check issuer name, anassociated check issuer's location, and the associated check issuer'schecking account.
 10. The method of claim 9, wherein identifying checkissuers in a desired geographical location further comprises identifyingcheck issuers within a desired proximity of a check-cashing entity. 11.The method of claim 9, wherein identifying check issuers in a desiredgeographical location further comprises identifying check issuers withina desired region defined by at least one of the set consisting of: zipcode, city, county, state, telephone area code, and MetropolitanStatistical Area (MSA).
 12. The method of claim 9, wherein identifyingcheck issuers in a desired geographical location comprises identifyingcheck issuers from any geographical location.
 13. The method of claim 9,further comprising the acts of: in response to receiving a request tocash a check for which the repository of records does not holdassociated check issuer information, requesting from a check-cashingentity that is processing the request, information about at least oneof: a check issuer name, a check issuer bank account identification, andcheck issuer location information; and adding check issuer informationreceived from the check-cashing entity to the repository.
 14. The methodof claim 13, wherein requesting information from a check-cashing entitycomprises displaying a prompt to an operator of a point-of-sale deviceat the check-cashing entity to input the requested information.
 15. Acomputer-accessible storage medium, wherein the storage medium storesrecords of information about check issuers and records of informationabout check-cashing entities, a record about a check issuer comprising acheck issuer identifier and location information associated with thecheck issuer, a record about a check-cashing identity comprising anidentifier for the check-cashing identity and location informationassociated with the check-cashing identity.
 16. The computer-accessiblestorage medium of claim 15, wherein the check issuer identifiercomprises at least one of: a check issuer name and an identifier for achecking account associated with the check issuer.
 17. Thecomputer-accessible storage medium of claim 16, wherein the identifiersfor checking accounts associated with the check issuers identifychecking accounts from a plurality of financial institutions.
 18. Thecomputer-accessible storage medium of claim 15, further comprisinginformation that correlates the check issuer location information andthe check-cashing entity location information.
 19. Thecomputer-accessible storage medium of claim 15, wherein a portion of therecords of information about check issuers comprises informationobtained from check issuers and a portion of the records of informationabout check issuers comprises information obtained from check-cashingentities.
 20. The computer-accessible storage medium of claim 19,wherein the portion of records obtained from check issuers compriserecords associated with check issuers in a desired geographic location.21. The computer-accessible storage medium of claim 19, wherein theportion of records obtained from check-cashing entities comprise recordsobtained during check-cashing transactions for which associated checkissuer information was not available in the storage medium prior to thecheck-cashing transaction.
 22. A method of accessing locationinformation for a check transaction, the method comprising: obtainingfrom a check information about an account associated with the check; andusing the account information to access stored information about a payorassociated with the account and about a payor location.
 23. The methodof claim 22, wherein obtaining information about an account comprisesreading magnetic ink character recognition (MICR) line information fromthe face of the check and extracting an identifying number for theaccount from the MICR line information.
 24. A method of compiling acomputer-accessible repository of location information about issuers ofnegotiable instruments, the method comprising: identifying issuers ofnegotiable instruments in a desired geographical location; obtainingfrom the issuers of negotiable instruments identifiers associated withthe negotiable instruments; and compiling on a computer-accessiblestorage medium a repository of records, wherein a record comprisesinformation to identify a name associated with an issuer of negotiableinstruments, an associated issuer location, and the associatedidentifiers associated with the negotiable instruments.
 25. The methodof claim 24, wherein identifying issuers of negotiable instruments in adesired geographical location further comprises identifying issuerswithin a desired proximity of a check-cashing entity.
 26. The method ofclaim 24, wherein identifying issuers of negotiable instruments in adesired geographical location further comprises identifying issuers ofnegotiable instruments within a desired region defined by at least oneof the set consisting of: zip code, city, county, state, telephone areacode, and Metropolitan Statistical Area (MSA).
 27. The method of claim24, wherein identifying issuers of negotiable instruments in a desiredgeographical location comprises identifying issuers of negotiableinstruments from any geographical location.
 28. A computer-accessiblestorage medium, wherein the storage medium stores records of informationabout issuers of negotiable financial instruments and records ofinformation about check-cashing entities, a record about an issuer of anegotiable financial instrument comprising an issuer identifier andlocation information associated with the issuer, a record about acheck-cashing identity comprising an identifier for the check-cashingidentity and location information associated with the check-cashingidentity.
 29. A system for compiling a computer-accessible repository ofcheck issuer location information for use in check transaction riskassessment, the system comprising: means for identifying check issuersin a desired geographical location; and means for compiling on acomputer-accessible storage medium a repository of records, wherein arecord comprises information to identify a check issuer name, anassociated check issuer location, and an associated check issuerchecking account, and wherein the checking account is an account drawnon by the check issuer for issuing checks.
 30. A computer-accessiblestorage medium comprising information that associates check issuer bankaccount information with check issuer location information andcheck-cashing entity location information.